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21 pages, 2908 KiB

Open AccessArticle

Fully Automatic Camera for Personalized Highlight Generation in Sporting Events

by Robbe Decorte, Jelle De Bock, Joachim Taelman, Maarten Slembrouck and Steven Verstockt

Sensors 2024, 24(3), 736; https://doi.org/10.3390/s24030736 - 23 Jan 2024

Cited by 1 | Viewed by 1045

Abstract

Personally curated content in short-form video formats provides added value for participants and spectators but is often disregarded in lower-level events because it is too labor-intensive to create or is not recorded at all. Our smart sensor-driven tripod focuses on supplying a unified [...] Read more.

Personally curated content in short-form video formats provides added value for participants and spectators but is often disregarded in lower-level events because it is too labor-intensive to create or is not recorded at all. Our smart sensor-driven tripod focuses on supplying a unified sensor and video solution to capture personalized highlights for participants in various sporting events with low computational and hardware costs. The relevant parts of the video for each participant are automatically determined by using the timestamps of his/her received sensor data. This is achieved through a customizable clipping mechanism that processes and optimizes both video and sensor data. The clipping mechanism is driven by sensing nearby signals of Adaptive Network Topology (ANT+) capable devices worn by the athletes that provide both locality information and identification. The device was deployed and tested in an amateur-level cycling race in which it provided clips with a detection rate of 92.9%. The associated sensor data were used to automatically extract peloton passages and report riders’ positions on the course, as well as which participants were grouped together. Insights derived from sensor signals can be processed and published in real time, and an upload optimization scheme is proposed that can provide video clips for each rider a maximum of 5 min after the passage if video upload is enabled. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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31 pages, 1199 KiB

Open AccessArticle

A Hierarchical Multitask Learning Approach for the Recognition of Activities of Daily Living Using Data from Wearable Sensors

by Muhammad Adeel Nisar, Kimiaki Shirahama, Muhammad Tausif Irshad, Xinyu Huang and Marcin Grzegorzek

Sensors 2023, 23(19), 8234; https://doi.org/10.3390/s23198234 - 3 Oct 2023

Cited by 3 | Viewed by 1694

Abstract

Machine learning with deep neural networks (DNNs) is widely used for human activity recognition (HAR) to automatically learn features, identify and analyze activities, and to produce a consequential outcome in numerous applications. However, learning robust features requires an enormous number of labeled data. [...] Read more.

Machine learning with deep neural networks (DNNs) is widely used for human activity recognition (HAR) to automatically learn features, identify and analyze activities, and to produce a consequential outcome in numerous applications. However, learning robust features requires an enormous number of labeled data. Therefore, implementing a DNN either requires creating a large dataset or needs to use the pre-trained models on different datasets. Multitask learning (MTL) is a machine learning paradigm where a model is trained to perform multiple tasks simultaneously, with the idea that sharing information between tasks can lead to improved performance on each individual task. This paper presents a novel MTL approach that employs combined training for human activities with different temporal scales of atomic and composite activities. Atomic activities are basic, indivisible actions that are readily identifiable and classifiable. Composite activities are complex actions that comprise a sequence or combination of atomic activities. The proposed MTL approach can help in addressing challenges related to recognizing and predicting both atomic and composite activities. It can also help in providing a solution to the data scarcity problem by simultaneously learning multiple related tasks so that knowledge from each task can be reused by the others. The proposed approach offers advantages like improved data efficiency, reduced overfitting due to shared representations, and fast learning through the use of auxiliary information. The proposed approach exploits the similarities and differences between multiple tasks so that these tasks can share the parameter structure, which improves model performance. The paper also figures out which tasks should be learned together and which tasks should be learned separately. If the tasks are properly selected, the shared structure of each task can help it learn more from other tasks. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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28 pages, 70008 KiB

Open AccessArticle

Individual Locating of Soccer Players from a Single Moving View

by Adrien Maglo, Astrid Orcesi, Julien Denize and Quoc Cuong Pham

Sensors 2023, 23(18), 7938; https://doi.org/10.3390/s23187938 - 16 Sep 2023

Cited by 6 | Viewed by 3850

Abstract

Positional data in team sports is key in evaluating the players’ individual and collective performances. When the sole source of data is a broadcast-like video of the game, an efficient video tracking method is required to generate this data. This article describes a [...] Read more.

Positional data in team sports is key in evaluating the players’ individual and collective performances. When the sole source of data is a broadcast-like video of the game, an efficient video tracking method is required to generate this data. This article describes a framework that extracts individual soccer player positions on the field. It is based on two main components. As in broadcast-like videos of team sport games, the camera view moves to follow the action and a sport field registration method estimates the homography between the pitch and the frame space. Our method estimates the positions of key points sampled on the pitch thanks to an encoder–decoder architecture. The attention mechanisms of the encoder, based on a vision transformer, captures characteristic pitch features globally in the frames. A multiple person tracker generates tracklets in the frame space by associating, with bipartite matching, the player detections between the current and the previous frames thanks to Intersection-Over-Union and distance criteria. Tracklets are then iteratively merged with appearance criteria thanks to a re-identification model. This model is fine-tuned in a self-supervised way on the player thumbnails of the video sample to specifically recognize the fine identification details of each player. The player positions in the frames projected by the homographies allow the obtaining of the real position of the players on the pitch at every moment of the video. We experimentally evaluate our sport field registration method and our 2D player tracker on public datasets. We demonstrate that they both outperform previous works for most metrics. Our 2D player tracker was also awarded first place at the SoccerNet tracking challenge in 2022 and 2023. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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13 pages, 928 KiB

Open AccessArticle

Acute Recovery after a Fatigue Protocol Using a Recovery Sports Legging: An Experimental Study

by Gonçalo Silva, Márcio Goethel, Leandro Machado, Filipa Sousa, Mário Jorge Costa, Pedro Magalhães, Carlos Silva, Marta Midão, André Leite, Suse Couto, Ricardo Silva, João Paulo Vilas-Boas and Ricardo Jorge Fernandes

Sensors 2023, 23(17), 7634; https://doi.org/10.3390/s23177634 - 3 Sep 2023

Cited by 3 | Viewed by 2539

Abstract

Enhancing recovery is a fundamental component of high-performance sports training since it enables practitioners to potentiate physical performance and minimise the risk of injuries. Using a new sports legging embedded with an intelligent system for electrostimulation, localised heating and compression (completely embodied into [...] Read more.

Enhancing recovery is a fundamental component of high-performance sports training since it enables practitioners to potentiate physical performance and minimise the risk of injuries. Using a new sports legging embedded with an intelligent system for electrostimulation, localised heating and compression (completely embodied into the textile structures), we aimed to analyse acute recovery following a fatigue protocol. Surface electromyography- and torque-related variables were recorded on eight recreational athletes. A fatigue protocol conducted in an isokinetic dynamometer allowed us to examine isometric torque and consequent post-exercise acute recovery after using the sports legging. Regarding peak torque, no differences were found between post-fatigue and post-recovery assessments in any variable; however, pre-fatigue registered a 16% greater peak torque when compared with post-fatigue for localised heating and compression recovery methods. Our data are supported by recent meta-analyses indicating that individual recovery methods, such as localised heating, electrostimulation and compression, are not effective to recover from a fatiguing exercise. In fact, none of the recovery methods available through the sports legging tested was effective in acutely recovering the torque values produced isometrically. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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13 pages, 1047 KiB

Open AccessArticle

WARNING: A Wearable Inertial-Based Sensor Integrated with a Support Vector Machine Algorithm for the Identification of Faults during Race Walking

by Juri Taborri, Eduardo Palermo and Stefano Rossi

Sensors 2023, 23(11), 5245; https://doi.org/10.3390/s23115245 - 31 May 2023

Cited by 2 | Viewed by 1475

Abstract

Due to subjectivity in refereeing, the results of race walking are often questioned. To overcome this limitation, artificial-intelligence-based technologies have demonstrated their potential. The paper aims at presenting WARNING, an inertial-based wearable sensor integrated with a support vector machine algorithm to automatically identify [...] Read more.

Due to subjectivity in refereeing, the results of race walking are often questioned. To overcome this limitation, artificial-intelligence-based technologies have demonstrated their potential. The paper aims at presenting WARNING, an inertial-based wearable sensor integrated with a support vector machine algorithm to automatically identify race-walking faults. Two WARNING sensors were used to gather the 3D linear acceleration related to the shanks of ten expert race-walkers. Participants were asked to perform a race circuit following three race-walking conditions: legal, illegal with loss-of-contact and illegal with knee-bent. Thirteen machine learning algorithms, belonging to the decision tree, support vector machine and k-nearest neighbor categories, were evaluated. An inter-athlete training procedure was applied. Algorithm performance was evaluated in terms of overall accuracy, F1 score and G-index, as well as by computing the prediction speed. The quadratic support vector was confirmed to be the best-performing classifier, achieving an accuracy above 90% with a prediction speed of 29,000 observations/s when considering data from both shanks. A significant reduction of the performance was assessed when considering only one lower limb side. The outcomes allow us to affirm the potential of WARNING to be used as a referee assistant in race-walking competitions and during training sessions. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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25 pages, 3839 KiB

Open AccessArticle

Comparison of Grip Strength, Forearm Muscle Activity, and Shock Transmission between the Forehand Stroke Technique of Experienced and Recreational Tennis Players Using a Novel Wearable Device

by Chantelle Jean Rigozzi, Gareth A. Vio and Philip Poronnik

Sensors 2023, 23(11), 5146; https://doi.org/10.3390/s23115146 - 28 May 2023

Cited by 5 | Viewed by 3423

Abstract

Upper limb tennis injuries are primarily chronic, resulting from repetitive overuse. We developed a wearable device which simultaneously measures risk factors (grip strength, forearm muscle activity, and vibrational data) associated with elbow tendinopathy development resulting from tennis players’ technique. We tested the device [...] Read more.

Upper limb tennis injuries are primarily chronic, resulting from repetitive overuse. We developed a wearable device which simultaneously measures risk factors (grip strength, forearm muscle activity, and vibrational data) associated with elbow tendinopathy development resulting from tennis players’ technique. We tested the device on experienced (n = 18) and recreational (n = 22) tennis players hitting forehand cross-court at both flat and topspin spin levels under realistic playing conditions. Using statistical parametric mapping analysis, our results showed that all players showed a similar level of grip strength at impact, regardless of spin level, and the grip strength at impact did not influence the percentage of impact shock transfer to the wrist and elbow. Experienced players hitting with topspin exhibited the highest ball spin rotation, low-to-high swing path brushing action, and shock transfer to the wrist and elbow compared to the results obtained while hitting the ball flat, or when compared to the results obtained from recreational players. Recreational players exhibited significantly higher extensor activity during most of the follow through phase compared to the experienced players for both spin levels, potentially putting them at greater risk for developing lateral elbow tendinopathy. We successfully demonstrated that wearable technologies can be used to measure risk factors associated with elbow injury development in tennis players under realistic playing conditions. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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17 pages, 7160 KiB

Open AccessArticle

Discovery and Characterisation of Forward Line Formations at Centre Bounces in the Australian Football League

by Daylon Seakins, Paul B. Gastin, Karl Jackson, Matthew Gloster, Aaron Brougham and David L. Carey

Sensors 2023, 23(10), 4891; https://doi.org/10.3390/s23104891 - 19 May 2023

Viewed by 2213

Abstract

The extent of player formation usage and the characteristics of player arrangements are not well understood in Australian football, unlike other team-based invasion sports. Using player location data from all centre bounces in the 2021 Australian Football League season; this study described the [...] Read more.

The extent of player formation usage and the characteristics of player arrangements are not well understood in Australian football, unlike other team-based invasion sports. Using player location data from all centre bounces in the 2021 Australian Football League season; this study described the spatial characteristics and roles of players in the forward line. Summary metrics indicated that teams differed in how spread out their forward players were (deviation away from the goal-to-goal axis and convex hull area) but were similar with regard to the centroid of player locations. Cluster analysis, along with visual inspection of player densities, clearly showed the presence of different repeated structures or formations used by teams. Teams also differed in their choice of player role combinations in forward lines at centre bounces. New terminology was proposed to describe the characteristics of forward line formations used in professional Australian Football. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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13 pages, 1519 KiB

Open AccessArticle

Highlighting Shooting Opportunities in Football

by Ilias Loutfi, Luis Ignacio Gómez-Jordana, Angel Ric, João Milho and Pedro Passos

Sensors 2023, 23(9), 4244; https://doi.org/10.3390/s23094244 - 24 Apr 2023

Cited by 2 | Viewed by 2558

Abstract

The purpose of the present study was to create a two-dimensional model which illustrates a landscape of shooting opportunities at goal during a competitive football match. For that purpose, we analysed exemplar attacking subphases of each team when the ball was in the [...] Read more.

The purpose of the present study was to create a two-dimensional model which illustrates a landscape of shooting opportunities at goal during a competitive football match. For that purpose, we analysed exemplar attacking subphases of each team when the ball was in the last 30 m of the field. The player’s positional data (x and y coordinates) and the ball were captured at 25 fps and processed to create heatmaps that illustrated the shooting opportunities that were available in the first and second half in different field areas. Moreover, the time that the shooting opportunities were available was estimated. Results show that in the observed match, most of the shooting opportunities lasted between 1 and 2 s, with only a few opportunities lasting more than 2 s. The shooting opportunities did not display a homogenous distribution over the field. The obtained heatmaps provide valuable and specific information about each team’s shooting opportunities, allowing the identification of the most vulnerable areas. Additionally, the amount, duration, and location of the shooting opportunities have shown significant differences between teams. This customizable model is sensitive to the features of shooting opportunities and can be used in real-time video analysis for individual and collective performance analysis. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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15 pages, 1996 KiB

Open AccessArticle

Using Arterial Pulse and Laser Doppler Analyses to Discriminate between the Cardiovascular Effects of Different Running Levels

by Yi-Jia Lin, Chia-Chien Lee, Tzu-Wei Huang, Wei-Chun Hsu, Li-Wei Wu, Chen-Chun Lin and Hsin Hsiu

Sensors 2023, 23(8), 3855; https://doi.org/10.3390/s23083855 - 10 Apr 2023

Viewed by 1792

Abstract

Background and Aims: Running can induce advantageous cardiovascular effects such as improved arterial stiffness and blood-supply perfusion. However, the differences between the vascular and blood-flow perfusion conditions under different levels of endurance-running performance remains unclear. The present study aimed to assess the vascular [...] Read more.

Background and Aims: Running can induce advantageous cardiovascular effects such as improved arterial stiffness and blood-supply perfusion. However, the differences between the vascular and blood-flow perfusion conditions under different levels of endurance-running performance remains unclear. The present study aimed to assess the vascular and blood-flow perfusion conditions among 3 groups (44 male volunteers) according to the time taken to run 3 km: Level 1, Level 2, and Level 3. Methods: The radial blood pressure waveform (BPW), finger photoplethygraphy (PPG), and skin-surface laser-Doppler flowmetry (LDF) signals of the subjects were measured. Frequency-domain analysis was applied to BPW and PPG signals; time- and frequency-domain analyses were applied to LDF signals. Results: Pulse waveform and LDF indices differed significantly among the three groups. These could be used to evaluate the advantageous cardiovascular effects provided by long-term endurance-running training, such as vessel relaxation (pulse waveform indices), improvement in blood supply perfusion (LDF indices), and changes in cardiovascular regulation activities (pulse and LDF variability indices). Using the relative changes in pulse-effect indices, we achieved almost perfect discrimination between Level 3 and Level 2 (AUC = 0.878). Furthermore, the present pulse waveform analysis could also be used to discriminate between the Level-1 and Level-2 groups. Conclusions: The present findings contribute to the development of a noninvasive, easy-to-use, and objective evaluation technique for the cardiovascular benefits of prolonged endurance-running training. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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14 pages, 5436 KiB

Open AccessArticle

Surrogate Modelling for Oxygen Uptake Prediction Using LSTM Neural Network

by Pavel Davidson, Huy Trinh, Sakari Vekki and Philipp Müller

Sensors 2023, 23(4), 2249; https://doi.org/10.3390/s23042249 - 16 Feb 2023

Cited by 2 | Viewed by 2303

Abstract

Oxygen uptake (

\dot{V} O

_{2}

) is an important metric in any exercise test including walking and running. It can be measured using portable spirometers or metabolic analyzers. Those devices are, however, not suitable for constant use by consumers due to [...] Read more.

Oxygen uptake (

\dot{V} O

_{2}

) is an important metric in any exercise test including walking and running. It can be measured using portable spirometers or metabolic analyzers. Those devices are, however, not suitable for constant use by consumers due to their costs, difficulty of operation and their intervening in the physical integrity of their users. Therefore, it is important to develop approaches for the indirect estimation of

\dot{V} O

_{2}

-based measurements of motion parameters, heart rate data and application-specific measurements from consumer-grade sensors. Typically, these approaches are based on linear regression models or neural networks. This study investigates how motion data contribute to

\dot{V} O

_{2}

estimation accuracy during unconstrained running and walking. The results suggest that a long short term memory (LSTM) neural network can predict oxygen consumption with an accuracy of 2.49 mL/min/kg (95% limits of agreement) based only on speed, speed change, cadence and vertical oscillation measurements from an inertial navigation system combined with a Global Positioning System (INS/GPS) device developed by our group, worn on the torso. Combining motion data and heart rate data can significantly improve the

\dot{V} O

_{2}

estimation resulting in approximately 1.7–1.9 times smaller prediction errors than using only motion or heart rate data. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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13 pages, 3234 KiB

Open AccessArticle

Definition of High-Risk Motion Patterns for Female ACL Injury Based on Football-Specific Field Data: A Wearable Sensors Plus Data Mining Approach

by Stefano Di Paolo, Eline M. Nijmeijer, Laura Bragonzoni, Alli Gokeler and Anne Benjaminse

Sensors 2023, 23(4), 2176; https://doi.org/10.3390/s23042176 - 15 Feb 2023

Cited by 6 | Viewed by 4171

Abstract

The aim of the present study was to investigate if the presence of anterior cruciate ligament (ACL) injury risk factors depicted in the laboratory would reflect at-risk patterns in football-specific field data. Twenty-four female footballers (14.9 ± 0.9 year) performed unanticipated cutting maneuvers [...] Read more.

The aim of the present study was to investigate if the presence of anterior cruciate ligament (ACL) injury risk factors depicted in the laboratory would reflect at-risk patterns in football-specific field data. Twenty-four female footballers (14.9 ± 0.9 year) performed unanticipated cutting maneuvers in a laboratory setting and on the football pitch during football-specific exercises (F-EX) and games (F-GAME). Knee joint moments were collected in the laboratory and grouped using hierarchical agglomerative clustering. The clusters were used to investigate the kinematics collected on field through wearable sensors. Three clusters emerged: Cluster 1 presented the lowest knee moments; Cluster 2 presented high knee extension but low knee abduction and rotation moments; Cluster 3 presented the highest knee abduction, extension, and external rotation moments. In F-EX, greater knee abduction angles were found in Cluster 2 and 3 compared to Cluster 1 (p = 0.007). Cluster 2 showed the lowest knee and hip flexion angles (p < 0.013). Cluster 3 showed the greatest hip external rotation angles (p = 0.006). In F-GAME, Cluster 3 presented the greatest knee external rotation and lowest knee flexion angles (p = 0.003). Clinically relevant differences towards ACL injury identified in the laboratory reflected at-risk patterns only in part when cutting on the field: in the field, low-risk players exhibited similar kinematic patterns as the high-risk players. Therefore, in-lab injury risk screening may lack ecological validity. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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15 pages, 2615 KiB

Open AccessArticle

Accuracy and Interpretation of the Acceleration from an Inertial Measurement Unit When Applied to the Sprint Performance of Track and Field Athletes

by Paulo Miranda-Oliveira, Marco Branco and Orlando Fernandes

Sensors 2023, 23(4), 1761; https://doi.org/10.3390/s23041761 - 4 Feb 2023

Cited by 3 | Viewed by 2890

Abstract

In this study, we aimed to assess sprinting using a developed instrument encompassing an inertial measurement unit (IMU) in order to analyze athlete performance during the sprint, as well as to determine the number of steps, ground contact time, flight time, and step [...] Read more.

In this study, we aimed to assess sprinting using a developed instrument encompassing an inertial measurement unit (IMU) in order to analyze athlete performance during the sprint, as well as to determine the number of steps, ground contact time, flight time, and step time using a high-speed camera as a reference. Furthermore, we correlated the acceleration components (XYZ) and acceleration ratio with the performance achieved in each split time obtained using photocells. Six athletes (four males and two females) ran 40 m with the IMU placed on their fifth lumbar vertebra. The accuracy was measured through the mean error (standard deviation), correlation (r), and comparison tests. The device could identify 88% to 98% of the number of steps. The GCT, flight time, and step time had mean error rates of 0.000 (0.012) s, 0.010 (0.011) s, and 0.009 (0.009) s when compared with the high-speed camera, respectively. The step time showed a correlation rate of r = 0.793 (p = 0.001) with no statistical differences, being the only parameter with high accuracy. Additionally, we showed probable symmetries, and through linear regression models identified that higher velocities result in the maximum anteroposterior acceleration, mainly over 0–40 m. Our device based on a Wi-Fi connection can determine the step time with accuracy and can show asymmetries, making it essential for coaches and medical teams. A new feature of this study was that the IMUs allowed us to understand that anteroposterior acceleration is associated with the best performance during the 40 m sprint test. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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12 pages, 1857 KiB

Open AccessArticle

Effect of Hamstring Tightness and Fatigue on Dynamic Stability and Agility in Physically Active Young Men

by Alberto Encarnación-Martínez, Antonio García-Gallart, Pedro Pérez-Soriano, Ignacio Catalá-Vilaplana, Julia Rizo-Albero and Roberto Sanchis-Sanchis

Sensors 2023, 23(3), 1633; https://doi.org/10.3390/s23031633 - 2 Feb 2023

Cited by 2 | Viewed by 4389

Abstract

Hamstring extensibility has been defined as a factor to diminished dynamic stability and therefore increased risk of injury. The purpose of this study was to analyse the effects of hamstring tightness and fatigue on dynamic stability and agility. Nineteen participants were divided between [...] Read more.

Hamstring extensibility has been defined as a factor to diminished dynamic stability and therefore increased risk of injury. The purpose of this study was to analyse the effects of hamstring tightness and fatigue on dynamic stability and agility. Nineteen participants were divided between the normal extensibility group (NEG) (n = 9, 82.2° ± 12.4°) and hamstrings tightness group (HTG) (n = 10, 64° ± 4.9°) using the passive straight leg raise test. To analyse dynamic stability and agility, they performed the modified Star Excursion Balance Test (mSEBT) and Dynamic Postural Stability Index (DPSI), and hexagon agility test, respectively, before and after a fatigue protocol. A two-way repeated measures ANOVA was used to determine differences among conditions: NEG vs. HTG, and rested vs. fatigued. HTG showed a significantly lower reach in the anterior direction in the mSEBT in pre- and post-fatigue than NEG. Participants in the NEG showed poor stability after landing in the mediolateral direction on DPSI post-fatigue. No significant changes were found in agility related with the group nor fatigue state. Participants with hamstring extensibility reduction has no differences in dynamic stability after landing nor agility after fatigue test, but significantly affects reaching distances during one-leg balance. As a conclusion, a reduction in range of motion in HTG was observed, but no other effects were observed on performance and dynamic stability after a local fatigue protocol depending on hamstring extensibility. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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16 pages, 3447 KiB

Open AccessArticle

Wearables and Machine Learning for Improving Runners’ Motivation from an Affective Perspective

by Sandra Baldassarri, Jorge García de Quirós, José Ramón Beltrán and Pedro Álvarez

Sensors 2023, 23(3), 1608; https://doi.org/10.3390/s23031608 - 1 Feb 2023

Cited by 2 | Viewed by 2434

Abstract

Wearable technology is playing an increasing role in the development of user-centric applications. In the field of sports, this technology is being used to implement solutions that improve athletes’ performance, reduce the risk of injury, or control fatigue, for example. Emotions are involved [...] Read more.

Wearable technology is playing an increasing role in the development of user-centric applications. In the field of sports, this technology is being used to implement solutions that improve athletes’ performance, reduce the risk of injury, or control fatigue, for example. Emotions are involved in most of these solutions, but unfortunately, they are not monitored in real-time or used as a decision element that helps to increase the quality of training sessions, nor are they used to guarantee the health of athletes. In this paper, we present a wearable and a set of machine learning models that are able to deduce runners’ emotions during their training. The solution is based on the analysis of runners’ electrodermal activity, a physiological parameter widely used in the field of emotion recognition. As part of the DJ-Running project, we have used these emotions to increase runners’ motivation through music. It has required integrating the wearable and the models into the DJ-Running mobile application, which interacts with the technological infrastructure of the project to select and play the most suitable songs at each instant of the training. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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12 pages, 2610 KiB

Open AccessArticle

Timing in Lower Limb Complex Movement Tests for DanceSport Athletes: Relation between FitLight Trainer and IMU Measurements

by Marija Prelević, Milivoj Dopsaj and Sara Stančin

Sensors 2023, 23(3), 1456; https://doi.org/10.3390/s23031456 - 28 Jan 2023

Cited by 6 | Viewed by 2208

Abstract

We examine the relation between two devices used in measuring the timing in lower limb complex movement tests for DanceSport athletes, an inertial measurement unit (IMU) and a FitLight Trainer device, with the latter regarded as the gold standard method in the field. [...] Read more.

We examine the relation between two devices used in measuring the timing in lower limb complex movement tests for DanceSport athletes, an inertial measurement unit (IMU) and a FitLight Trainer device, with the latter regarded as the gold standard method in the field. Four tests are selected to cover the lower limb movements. The research sample comprises 21 experienced dancers from different dance disciplines, performing the four tests with each of their lower limbs. Compared using concurrent validity, the two devices used show great agreement for estimating the total tests’ run times, with interclass correlation coefficients between 0.967 and 0.994 for all tests. This agreement is additionally confirmed by Bland–Altman plots. As an alternative to other devices, the IMU sensor has proven to be a precise and suitable device for measuring timing and testing in sports. Its mobility, light weight, and size are advantages of this device in addition to measurement accuracy. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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16 pages, 1328 KiB

Open AccessArticle

Visual Behaviours of Expert Padel Athletes When Playing on Court: An In Situ Approach with a Portable Eye Tracker

by Carlos Espino Palma, Vicente Luis del Campo and Diego Muñoz Marín

Sensors 2023, 23(3), 1438; https://doi.org/10.3390/s23031438 - 28 Jan 2023

Cited by 5 | Viewed by 2859

Abstract

Eye-tracking research has allowed the characterisation of gaze behaviours in some racket sports (e.g., tennis, badminton), both in controlled laboratory settings and in real-world scenarios. However, there are no studies about visual patterns displayed by athletes in padel. Method: The aim of this [...] Read more.

Eye-tracking research has allowed the characterisation of gaze behaviours in some racket sports (e.g., tennis, badminton), both in controlled laboratory settings and in real-world scenarios. However, there are no studies about visual patterns displayed by athletes in padel. Method: The aim of this exploratory case study was to address the visual behaviours of eight young expert padel athletes when playing match games on a padel court. Specifically, their gaze behaviours were examined with an in situ approach while returned trays/smashes, serves, and volleys were performed by their counterparts. Gaze patterns were registered with an SMI Eye Tracking Glasses 2 Wireless. Results: The participants’ gaze was mainly focused on the ball-flight trajectory and on the upper body of the opponents because they were the two visual locations with a larger number of fixations and longer fixation time. No differences were found in these variables for each type of visual location when the three return situations were compared, or independently of them. Conclusions: Padel players displayed a similar gaze behaviour during different representative return situations. This visual pattern was characterised by fixating at the ball and some opponents’ upper kinematics (head, shoulders, trunk, and the region of arm–hand–racket) to perform real interceptive actions while playing against them on a padel court. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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10 pages, 831 KiB

Open AccessArticle

The Influence of Pitch Dimensions during Small-Sided Games to Reach Match Physical and Physiological Demands on the Youth Soccer Players

by Alfonso Castillo-Rodríguez, Álvaro Durán-Salas, Jesús Vicente Giménez, Wanesa Onetti-Onetti and Luis Suárez-Arrones

Sensors 2023, 23(3), 1299; https://doi.org/10.3390/s23031299 - 23 Jan 2023

Cited by 5 | Viewed by 3057

Abstract

The aims of this study were to (i) analyze the physical and physiological responses of four matches competition and (ii) to investigate the relationships among three different pitch dimensions of small-sided game (SSG) on the youth soccer players. Fifteen male U19 soccer players [...] Read more.

The aims of this study were to (i) analyze the physical and physiological responses of four matches competition and (ii) to investigate the relationships among three different pitch dimensions of small-sided game (SSG) on the youth soccer players. Fifteen male U19 soccer players (age 17.3 ± 0.5 years, height 175.7 ± 5.6 cm, weight 68.5 ± 8.6 kg, playing experience 7.8 ± 1.4 years) were randomly assigned to three play areas: small (50 m²), medium (SSG-m, 150 m²) and large (SSG-l, 250 m²) area per player including goalkeeper. During the 4-week intervention, both groups performed three sets of 8 min with a passive rest period of 5 min between games. Differences in time-motion characteristics of players were measured with the Global Positioning System and assessed using a repeated measures ANOVA to compare the three game conditions and the magnitude-based inference to evaluate the pairwise comparison effects. The results showed that only the variables distance covered between 7.0–12.9 km·h⁻¹ was not statistically significantly different among game conditions (p < 0.05; η = 0.21; small) and physiological response (i.e., hear rate of playing time spent 85–89% HR_max) also showed differences (p < 0.05; η = 0.25; small). The responses in SSG-m and SSG-l established them ass the format sizes ideal for replicating the physical responses during match competition. These findings could provide relevant information for coaches for use adequate pitch size (areas of 150 m² and 250 m²) to reach the match-play scenarios found in match competition. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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11 pages, 1334 KiB

Open AccessArticle

Feasibility of a Novel Therapist-Assisted Feedback System for Gait Training in Parkinson’s Disease

by Carla Silva-Batista, Graham Harker, Rodrigo Vitorio, Fay B. Horak, Patricia Carlson-Kuhta, Sean Pearson, Jess VanDerwalker, Mahmoud El-Gohary and Martina Mancini

Sensors 2023, 23(1), 128; https://doi.org/10.3390/s23010128 - 23 Dec 2022

Cited by 3 | Viewed by 2407

Abstract

We tested the feasibility of one session of treadmill training using a novel physical therapist assisted system (Mobility Rehab) using wearable sensors on the upper and lower limbs of 10 people with Parkinson’s disease (PD). Participants performed a 2-min walk overground before and [...] Read more.

We tested the feasibility of one session of treadmill training using a novel physical therapist assisted system (Mobility Rehab) using wearable sensors on the upper and lower limbs of 10 people with Parkinson’s disease (PD). Participants performed a 2-min walk overground before and after 15 min of treadmill training with Mobility Rehab, which included an electronic tablet (to visualize gait metrics) and five Opal sensors placed on both the wrists and feet and on the sternum area to measure gait and provide feedback on six gait metrics (foot-strike angle, trunk coronal range-of-motion (ROM), arm swing ROM, double-support duration, gait-cycle duration, and step asymmetry). The physical therapist used Mobility Rehab to select one or two gait metrics (from the six) to focus on during the treadmill training. Foot-strike angle (effect size (ES) = 0.56, 95% Confidence Interval (CI) = 0.14 to 0.97), trunk coronal RoM (ES = 1.39, 95% CI = 0.73 to 2.06), and arm swing RoM (ES = 1.64, 95% CI = 0.71 to 2.58) during overground walking showed significant and moderate-to-large ES following treadmill training with Mobility Rehab. Participants perceived moderate (60%) and excellent (30%) effects of Mobility Rehab on their gait. No adverse events were reported. One session of treadmill training with Mobility Rehab is feasible for people with mild-to-moderate PD. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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18 pages, 7870 KiB

Open AccessArticle

Quantification of Error Sources with Inertial Measurement Units in Sports

by Haye Kamstra, Erik Wilmes and Frans C. T. van der Helm

Sensors 2022, 22(24), 9765; https://doi.org/10.3390/s22249765 - 13 Dec 2022

Cited by 10 | Viewed by 2230

Abstract

Background: Inertial measurement units (IMUs) offer the possibility to capture the lower body motions of players of outdoor team sports. However, various sources of error are present when using IMUs: the definition of the body frames, the soft tissue artefact (STA) and the [...] Read more.

Background: Inertial measurement units (IMUs) offer the possibility to capture the lower body motions of players of outdoor team sports. However, various sources of error are present when using IMUs: the definition of the body frames, the soft tissue artefact (STA) and the orientation filter. Methods to minimize these errors are currently being used without knowing their exact influence on the various sources of errors. The goal of this study was to present a method to quantify each of the sources of error of an IMU separately. Methods: An optoelectronic system was used as a gold standard. Rigid marker clusters (RMCs) were designed to construct a rigid connection between the IMU and four markers. This allowed for the separate quantification of each of the sources of error. Ten subjects performed nine different football-specific movements, varying both in the type of movement, and in movement intensity. Results: The error of the definition of the body frames (11.3–18.7 deg RMSD), the STA (3.8–9.1 deg RMSD) and the error of the orientation filter (3.0–12.7 deg RMSD) were all quantified separately for each body segment. Conclusions: The error sources of IMU-based motion analysis were quantified separately. This allows future studies to quantify and optimize the effects of error reduction techniques. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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10 pages, 932 KiB

Open AccessArticle

A Comparison between High and Low Cuff Pressures on Muscle Oxygen Saturation and Recovery Responses Following Blood-Flow Restriction Resistance Exercise

by Sandro Bartolomei, Pasquale Montesanto, Ivan Malagoli Lanzoni, Giorgio Gatta, Matteo Cortesi and Silvia Fantozzi

Sensors 2022, 22(23), 9138; https://doi.org/10.3390/s22239138 - 25 Nov 2022

Cited by 2 | Viewed by 2603

Abstract

The aim of the study was to compare the recovery response and muscle oxygenation of a blood-flow restriction resistance exercise (BFR) session with high [HP: 80% of the arterial occlusion pressure (AOP)] and low cuff pressure (LP: 40% of AOP). Both exercise sessions [...] Read more.

The aim of the study was to compare the recovery response and muscle oxygenation of a blood-flow restriction resistance exercise (BFR) session with high [HP: 80% of the arterial occlusion pressure (AOP)] and low cuff pressure (LP: 40% of AOP). Both exercise sessions included 4 sets to failure at the barbell preacher curl exercise. Twelve resistance trained men (27.4 ± 5.0 years; 83.5 ± 11.6 kg; 176.6 ± 7.0 cm) performed each protocol in a counterbalanced, randomized order. Maximal isometric force, muscle morphology and muscle soreness of the biceps brachii muscle were assessed at baseline, 15-min, 60-min and 24-h post each testing session. In addition, muscle oxygen saturation (SmO₂) was assessed during each training session. A lower number of repetitions (p = 0.013) was detected in HP compared to LP. A lower SmO₂ (p < 0.001) was detected in the recovery time between the sets in HP (mean: 47.6 ± 15.7%) compared to LP (mean: 68.9 ± 7.2%). No differences between the two trials (p > 0.05) were noted for isometric force, muscle architecture and soreness at any timepoint. Results indicate that, despite a high cuff pressure may induce a more hypoxic condition compared to a lower cuff pressure, recovery responses may not be affected. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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13 pages, 1740 KiB

Open AccessArticle

Concurrent Validity and Reliability of Devices to Measure Jump Height in Men’s Handball Players

by Alejandro Soler-López, Antonio García-de-Alcaraz, Adrián Moreno-Villanueva and José Pino-Ortega

Sensors 2022, 22(23), 9070; https://doi.org/10.3390/s22239070 - 23 Nov 2022

Cited by 11 | Viewed by 2648

Abstract

Although there is a wide range of validated devices to measure vertical jump height, the degree of interchangeability among them is currently unknown. Aims: The purpose of this study was to examine the concurrent validity and reliability of multiple devices to measure jump [...] Read more.

Although there is a wide range of validated devices to measure vertical jump height, the degree of interchangeability among them is currently unknown. Aims: The purpose of this study was to examine the concurrent validity and reliability of multiple devices to measure jump height in men’s handball players. Methods: Sixteen players (age = 24.0 ± 3.7 years old) performed three types of jumps (n= 144—squat jump (SJ), countermovement jump (CMJ) and Abalakov jump (ABK)) on a contact platform (CHRONOJUMP^®) while simultaneously being measured with two inertial devices (WIMU^® and VERT^®) and recorded with a high-speed camera. Vertical jump height was analyzed according to each type of jump. Results: The t-test showed statistically significant differences (p = 0.001) between the contact platform (reference standard) and the rest of the tools that tended to overestimate jump height in all jumps. SJ and CMJ proved to be the jump tests with the most stable reliability values in all devices (ICC: 0.92–0.98), except in the comparison with VERT^®. Conclusions: Although all the analyzed devices proved to be valid and reliable in previous studies, they are not interchangeable. Therefore, it is suggested to always use the same type of device to evaluate vertical height jump. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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11 pages, 1186 KiB

Open AccessArticle

Test–Retest Reliability of Task Performance for Golf Swings of Medium- to High-Handicap Players

by Israel Villarrasa-Sapiña, Nuria Ortega-Benavent, Gonzalo Monfort-Torres, Jesús Ramon-Llin and Xavier García-Massó

Sensors 2022, 22(23), 9069; https://doi.org/10.3390/s22239069 - 23 Nov 2022

Cited by 7 | Viewed by 1754

Abstract

Background: Golf swing performance in medium- to high-handicap players must be reliably measured to use this variable in both research studies and in applied settings. Nevertheless, there are no studies published on this topic and test–retest evidence is only available for low-handicap players. [...] Read more.

Background: Golf swing performance in medium- to high-handicap players must be reliably measured to use this variable in both research studies and in applied settings. Nevertheless, there are no studies published on this topic and test–retest evidence is only available for low-handicap players. The aim of this study was to determine the number of attempts necessary to obtain a reliable measurement protocol for swing performance variables in medium- to high-handicap players. Methods: Ten amateur players (55.67 (13.64) years, 78.4 (11.4) kg, 1.75 (7.95) m) took part in a test–retest study in two experimental sessions one week apart. In each one, fifteen swings with a six iron and a driver were evaluated with a 3D Doppler tracking golf radar. Results: The results showed that variables related to side carry could not be reliably measured in medium- to high-handicap players in only fifteen trials (ICC < 0.26, SEM > 12.05 m and MDC > 33.41 m). The rest of the performance variables related to the club and ball trajectories could be reliably measured with a 3D Doppler radar with between seven and ten swings. Conclusions: At least seven swings are recommended for the driver and ten for the six iron to measure golf swing performance. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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10 pages, 648 KiB

Open AccessArticle

Sensor Location Matters When Estimating Player Workload for Baseball Pitching

by Cristine Agresta, Michael T. Freehill, Jessica Zendler, Georgia Giblin and Stephen Cain

Sensors 2022, 22(22), 9008; https://doi.org/10.3390/s22229008 - 21 Nov 2022

Cited by 2 | Viewed by 2345

Abstract

Estimating external workload in baseball pitchers is important for training and rehabilitation. Since current methods of estimating workload through pitch counts and rest days have only been marginally successful, clubs are looking for more sophisticated methods to quantify the mechanical loads experienced by [...] Read more.

Estimating external workload in baseball pitchers is important for training and rehabilitation. Since current methods of estimating workload through pitch counts and rest days have only been marginally successful, clubs are looking for more sophisticated methods to quantify the mechanical loads experienced by pitchers. Among these are the use of wearable systems. While wearables offer a promising solution, there remains a lack of standards or guidelines for how best to employ these devices. As a result, sensor location and workload calculation methods vary from system to system. This can influence workload estimates and blur their interpretation and utility when making decisions about training or returning to sport. The primary purpose of this study was to determine the extent to which sensor location influences workload estimate. A secondary purpose was to compare estimates using different workload calculations. Acceleration data from three sensor locations—trunk, throwing upper arm, and throwing forearm—were collected from ten collegiate pitchers as they threw a series of pitches during a single bullpen session. The effect of sensor location and pitch type was assessed in relation to four different workload estimates. Sensor location significantly influenced workload estimates. Workload estimates calculated from the forearm sensor were significantly different across pitch types. Whole-body workload measured from a trunk-mounted sensor may not adequately reflect the mechanical loads experienced at throwing arm segments. A sensor on the forearm was the most sensitive to differences in workloads across pitch types, regardless of the calculation method. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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10 pages, 1236 KiB

Open AccessArticle

Force Plate-Derived Countermovement Jump Normative Data and Benchmarks for Professional Rugby League Players

by John J. McMahon, Nicholas J. Ripley and Paul Comfort

Sensors 2022, 22(22), 8669; https://doi.org/10.3390/s22228669 - 10 Nov 2022

Cited by 9 | Viewed by 12806

Abstract

The countermovement jump (CMJ) is an important test in rugby league (RL), and the force plate is the recommended assessment device, as it permits the calculation of several variables that explain jump strategy, alongside jump height. The purpose of this study was to [...] Read more.

The countermovement jump (CMJ) is an important test in rugby league (RL), and the force plate is the recommended assessment device, as it permits the calculation of several variables that explain jump strategy, alongside jump height. The purpose of this study was to produce normative CMJ data and objective benchmarks for professional RL forwards and backs. Normative data for jump height, modified reactive strength index, and jump momentum are provided for 121 professional RL players (66 forwards and 55 backs) who completed CMJ testing on a portable force plate during preseason training. Standardized T-scores (scaled from 0 to 100) were calculated from the respective positional group mean and standard deviation to create CMJ performance bands that were combined with a qualitative description (ranging from extremely poor to excellent) and a traffic light system to facilitate data interpretation and objective benchmark setting by RL practitioners. The jump height and modified reactive strength index benchmarks were larger for the lighter backs, whereas the jump momentum benchmarks were larger for the heavier forwards. The presented novel approach to compiling and presenting normative data and objective benchmarks may also be applied to other data (i.e., from other tests or devices) and populations. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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13 pages, 4226 KiB

Open AccessArticle

Chronic and Acute Effects on Skin Temperature from a Sport Consisting of Repetitive Impacts from Hitting a Ball with the Hands

by Jose Luis Sánchez-Jiménez, Robert Tejero-Pastor, María del Carmen Calzadillas-Valles, Irene Jimenez-Perez, Rosa Maria Cibrián Ortiz de Anda, Rosario Salvador-Palmer and Jose Ignacio Priego-Quesada

Sensors 2022, 22(21), 8572; https://doi.org/10.3390/s22218572 - 7 Nov 2022

Cited by 1 | Viewed by 1871

Abstract

Valencian handball consists in hitting the ball with the hands and it may contribute to injury development on the hands. This study aimed to analyze skin temperature asymmetries and recovery after a cold stress test (CST) in professional players of Valencian handball before [...] Read more.

Valencian handball consists in hitting the ball with the hands and it may contribute to injury development on the hands. This study aimed to analyze skin temperature asymmetries and recovery after a cold stress test (CST) in professional players of Valencian handball before and after a competition. Thirteen professional athletes and a control group of ten physically active participants were measured. For both groups, infrared images were taken at the baseline condition; later they underwent a thermal stress test (pressing for 2 min with the palm of the hand on a metal plate) and then recovery images were taken. In athletes, the images were also taken after their competition. Athletes at baseline condition presented lower temperatures (p < 0.05) in the dominant hand compared with the non-dominant hand. There were asymmetries in all regions after their match (p < 0.05). After CST, a higher recovery rate was found after the game. The regions with the most significant differences in variation, asymmetries and recovery patterns were the index, middle and ring fingers, and the palm of the dominant hand. Taking into account that lower temperatures and the absence of temperature variation may be the consequence of a vascular adaptation, thermography could be used as a method to prevent injuries in athletes from Valencian handball. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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16 pages, 3943 KiB

Open AccessArticle

Reliability and Validity of Inertial Sensor Assisted Reaction Time Measurement Tools among Healthy Young Adults

by Brent Harper, Michael Shiraishi and Rahul Soangra

Sensors 2022, 22(21), 8555; https://doi.org/10.3390/s22218555 - 6 Nov 2022

Cited by 3 | Viewed by 2581

Abstract

The assessment of movement reaction time (RT) as a sideline assessment is a valuable biomarker for mild TBI or concussion. However, such assessments require controlled laboratory environments, which may not be feasible for sideline testing during a game. Body-worn wearable devices are advantageous [...] Read more.

The assessment of movement reaction time (RT) as a sideline assessment is a valuable biomarker for mild TBI or concussion. However, such assessments require controlled laboratory environments, which may not be feasible for sideline testing during a game. Body-worn wearable devices are advantageous as being cost-effective, easy to don and use, wirelessly transmit data, and ensure unhindered movement performance. This study aimed to develop a Drop-stick Test System (DTS) with a wireless inertial sensor and confirm its reliability for different standing conditions (Foam versus No Foam) and task types (Single versus Dual), and postures (Standing versus sitting). Fourteen healthy young participants (seven females, seven males; age 24.7 ± 2.6 years) participated in this study. The participants were asked to catch a falling stick attached to the sensor during a drop test. Reaction Times (RTs) were calculated from data for each trial from DTS and laboratory camera system (gold standard). Intraclass correlation coefficients (ICC 3,k) were computed to determine inter-instrument reliability. The RT measurements from participants using the camera system and sensor-based DTS showed moderate to good inter-instrument reliability with an overall ICC of 0.82 (95% CI 0.78–0.85). Bland–Altman plots and 95% levels of agreement revealed a bias where the DTS underestimated RT by approximately 50 ms. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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9 pages, 745 KiB

Open AccessArticle

Using Sensors for Player Development: Assessing Biomechanical Factors Related to Pitch Command and Velocity

by Cristine Agresta, Michael T. Freehill, Bryson Nakamura, Samuel Guadagnino and Stephen M. Cain

Sensors 2022, 22(21), 8488; https://doi.org/10.3390/s22218488 - 4 Nov 2022

Cited by 2 | Viewed by 2291

Abstract

Pitching biomechanical research is highly focused on injury prevention with little attention to how biomechanical data can facilitate skill development. The overall purpose of this study was to explore how sensor-derived segment kinematics and timing relate to command and ball velocity during baseball [...] Read more.

Pitching biomechanical research is highly focused on injury prevention with little attention to how biomechanical data can facilitate skill development. The overall purpose of this study was to explore how sensor-derived segment kinematics and timing relate to command and ball velocity during baseball pitching. We used a cross-sectional design to analyze a series of pitches thrown from 10 collegiate baseball pitchers. We collected biomechanical data from six inertial sensors, subjective command from the pitchers, and ball velocity from a radar device. Stepwise regression analyses were used to explore biomechanical variables associated with command for all pitches and ball velocity for fastballs only. We found that only peak forearm linear acceleration was significantly associated with command, whereas several segment kinematic measures were significantly associated with ball velocity. Our results suggest that different biomechanical variables are linked to specific pithing skills. Our findings suggest that end-effector (forearm) movement is more important for pitch command, whereas proximal-to-distal (pelvis, trunk, upper arm, forearm) segmental movement is important for ball velocity. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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9 pages, 1942 KiB

Open AccessCommunication

Wearable Inertial Sensor Approach for Postural Adjustment Assessments during Predictable Perturbations in Sport

by Manuela Brito Duarte, Anderson Antunes da Costa Moraes, Eduardo Veloso Ferreira, Gizele Cristina da Silva Almeida, André dos Santos Cabral, Anselmo de Athayde Costa e Silva, Daniela Rosa Garcez, Givago da Silva Souza and Bianca Callegari

Sensors 2022, 22(21), 8272; https://doi.org/10.3390/s22218272 - 28 Oct 2022

Cited by 4 | Viewed by 1678

Abstract

Introduction: Evidence supports the importance of efficient postural control to improve performance in sports. This involves the use of strategies such as anticipatory posture adjustments and compensatory adjustments. Technology makes analysis and assessments in sports cheaper, while being valid and reliable compared to [...] Read more.

Introduction: Evidence supports the importance of efficient postural control to improve performance in sports. This involves the use of strategies such as anticipatory posture adjustments and compensatory adjustments. Technology makes analysis and assessments in sports cheaper, while being valid and reliable compared to the gold-standard assessment equipment. Objectives: This article aimed to test the validity and reliability of signals extracted from the sensor’s accelerometer (Metamotion C), by comparing it to the data obtained from the gold-standard equipment (a three-dimensional video-motion-capture system). Design: Observational, cross-sectional study. Methods: We exposed 20 healthy young standing people to the pendulum impact paradigm, which consisted of predictable anteroposterior disturbances applied at the shoulder level. In order to measure this, we observed the acceleration of the center of mass in the anticipatory and compensatory phase of the disturbance and compared the signals of the two devices (Metamotion C and a motion-capture system). Results: The validation results showed the significant linear correlation of all variables with a moderate to large correlation of r ≥ 0.5 between the devices. In contrast, the reliability results between sessions obtained by filming were all significant and above 0.75, indicating excellent reliability. The APAonset variable had a reasonable to high intra-class correlation in the anticipatory phase. In the compensatory phase, the CPA_time variable showed an excellent correlation. Conclusions: Metamotion C proved reasonably valid and highly reliable in measuring the center of mass acceleration compared to the camera system in both the anticipatory and compensatory phases. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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14 pages, 1501 KiB

Open AccessArticle

Float like a Butterfly: Comparison between Off and On-Ice Torso Kinematics during the Butterfly Stance in Ice Hockey Goalkeepers

by Stuart A Evans, Rodrigo Bini, Gregory Davis and James Lee

Sensors 2022, 22(19), 7320; https://doi.org/10.3390/s22197320 - 27 Sep 2022

Cited by 1 | Viewed by 3840

Abstract

In ice hockey, the butterfly style/stance is a technique distinguished by the goalkeepers (goalie) dropping to their knees to block attempts to score. Although this goalie style has been around for many years, comparisons between on and off-ice attire has not been undertaken. [...] Read more.

In ice hockey, the butterfly style/stance is a technique distinguished by the goalkeepers (goalie) dropping to their knees to block attempts to score. Although this goalie style has been around for many years, comparisons between on and off-ice attire has not been undertaken. Therefore, this preliminary study compared differences in torso acceleration and energy expenditure by way of the Metabolic Equivalent of Task (MET) during off-ice and on-ice butterfly stances/saves. Seven participants each performed 8 on-ice butterfly saves/stances whilst wearing full hockey attire followed by 8 off-ice butterfly stances without wearing full hockey attire whilst torso acceleration was collected. The off-ice movement significantly increased vertical torso acceleration (p < 0.01, d > 0.90) with increased MET, compared to on-ice motion. Despite no significant difference in anteroposterior and mediolateral torso kinematics, vector magnitudes were significantly greater (p < 0.01, d > 0.90) when the stance was performed off-ice. The increased vertical acceleration observed when goalies performed the movement off-ice could be due to a failure to maintain adequate posture without the support of the external load. The results of this study may help inform off-ice training interventions for ice hockey goalkeeping. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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12 pages, 1145 KiB

Open AccessArticle

Can the Supido Radar Be Used for Measuring Ball Speed during Soccer Kicking? A Reliability and Concurrent Validity Study of a New Low-Cost Device

by David M. Díez-Fernández, David Rodríguez-Rosell, Federico Gazzo, Julián Giráldez, Rodrigo Villaseca-Vicuña and Jose A. Gonzalez-Jurado

Sensors 2022, 22(18), 7046; https://doi.org/10.3390/s22187046 - 17 Sep 2022

Cited by 5 | Viewed by 2709

Abstract

The aim was to analyze the reliability and validity of a low-cost instrument, based on a radar system, to quantify the kicking ball speed in soccer. A group of 153 male soccer players (under-13, n = 53; under-15, n = 54; under-18, n [...] Read more.

The aim was to analyze the reliability and validity of a low-cost instrument, based on a radar system, to quantify the kicking ball speed in soccer. A group of 153 male soccer players (under-13, n = 53; under-15, n = 54; under-18, n = 46) participated in this study. Each player performed three kicks on the goal in a standardized condition while the ball speed was measured with three different devices: one Radar Stalker ATS II^® (reference criterion) and two Supido Radar^® (Supido-front of the goal and Supido-back of the goal). The standard error of measurement (SEM) expressed as a coefficient of variation (CV) and the intraclass correlation coefficient (ICC) were employed for assessing the reliability of each instrument. Stalker and Supido-back showed very high absolute (CV = 4.0–5.4%) and relative (ICC = 0.945–0.958) reliability, whereas Supido-front resulted in moderate to low reliability scores (CV = 7.4–15%, ICC = 0.134–0.693). In addition, Lin’s concordance correlation coefficient (CCC) values revealed an ‘almost perfect’ agreement between Stalker and Supido-back for the average (r = 0.99) and maximal (r = 0.98) ball speed, regardless of the ball speed range analyzed. However, Supido-front resulted in a poor degree of concordance (CCC = 0.688) and a high magnitude of error (17.0–37.5 km·h⁻¹) with the reference Stalker radar gun. The Supido Radar^® placed behind the goal could be considered a reliable and valid device for measuring ball speed in soccer. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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14 pages, 1232 KiB

Open AccessArticle

A Week of Sleep Restriction Does Not Affect Nighttime Glucose Concentration in Healthy Adult Males When Slow-Wave Sleep Is Maintained

by Thomas G. Kontou, Charli Sargent and Gregory D. Roach

Sensors 2022, 22(18), 6962; https://doi.org/10.3390/s22186962 - 14 Sep 2022

Cited by 4 | Viewed by 2141

Abstract

The aim of this laboratory-based study was to examine the effect of sleep restriction on glucose regulation during nighttime sleep. Healthy males were randomly assigned to one of two conditions: 9 h in bed (n = 23, age = 24.0 year) or [...] Read more.

The aim of this laboratory-based study was to examine the effect of sleep restriction on glucose regulation during nighttime sleep. Healthy males were randomly assigned to one of two conditions: 9 h in bed (n = 23, age = 24.0 year) or 5 h in bed (n = 18, age = 21.9 year). Participants had a baseline night with 9 h in bed (23:00–08:00 h), then seven nights of 9 h (23:00–08:00 h) or 5 h (03:00–08:00 h) in bed. Participants were mostly seated during the daytime but had three bouts of treadmill walking (4 km·h⁻¹ for 10 min) at ~14:40 h, ~17:40 h, and ~20:40 h each day. On the baseline night and night seven, glucose concentration in interstitial fluid was assessed by using continuous glucose monitors, and sleep was assessed by using polysomnography. On night seven, compared to the 9 h group, the 5 h group obtained less total sleep (292 min vs. 465 min) and less REM sleep (81 min vs. 118 min), but their slow-wave sleep did not differ (119 min vs. 120 min), and their glucose concentration during sleep did not differ (5.1 mmol·L⁻¹ vs. 5.1 mmol·L⁻¹). These data indicate that sleep restriction does not cause elevated levels of circulating glucose during nighttime sleep when slow-wave sleep is maintained. In the future, it will be important to determine whether increased insulin is required to maintain circulating glucose at a normal level when sleep is restricted. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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17 pages, 5589 KiB

Open AccessArticle

A Comprehensive Analysis of the Validity and Reliability of the Perception Neuron Studio for Upper-Body Motion Capture

by Yiwei Wu, Kuan Tao, Qi Chen, Yinsheng Tian and Lixin Sun

Sensors 2022, 22(18), 6954; https://doi.org/10.3390/s22186954 - 14 Sep 2022

Cited by 15 | Viewed by 3304

Abstract

The Perception Neuron Studio (PNS) is a cost-effective and widely used inertial motion capture system. However, a comprehensive analysis of its upper-body motion capture accuracy is still lacking, before it is being applied to biomechanical research. Therefore, this study first evaluated the validity [...] Read more.

The Perception Neuron Studio (PNS) is a cost-effective and widely used inertial motion capture system. However, a comprehensive analysis of its upper-body motion capture accuracy is still lacking, before it is being applied to biomechanical research. Therefore, this study first evaluated the validity and reliability of this system in upper-body capturing and then quantified the system’s accuracy for different task complexities and movement speeds. Seven participants performed simple (eight single-DOF upper-body movements) and complex tasks (lifting a 2.5 kg box over the shoulder) at fast and slow speeds with the PNS and OptiTrack (gold-standard optical system) collecting kinematics data simultaneously. Statistical metrics such as CMC, RMSE, Pearson’s r, R², and Bland–Altman analysis were utilized to assess the similarity between the two systems. Test–retest reliability included intra- and intersession relations, which were assessed by the intraclass correlation coefficient (ICC) as well as CMC. All upper-body kinematics were highly consistent between the two systems, with CMC values 0.73–0.99, RMSE 1.9–12.5°, Pearson’s r 0.84–0.99, R² 0.75–0.99, and Bland–Altman analysis demonstrating a bias of 0.2–27.8° as well as all the points within 95% limits of agreement (LOA). The relative reliability of intra- and intersessions was good to excellent (i.e., ICC and CMC were 0.77–0.99 and 0.75–0.98, respectively). The paired t-test revealed that faster speeds resulted in greater bias, while more complex tasks led to lower consistencies. Our results showed that the PNS could provide accurate enough upper-body kinematics for further biomechanical performance analysis. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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7 pages, 724 KiB

Open AccessArticle

Evaluating the Typical Day-to-Day Variability of WHOOP-Derived Heart Rate Variability in Olympic Water Polo Athletes

by Clint R. Bellenger, Dean Miller, Shona L. Halson, Gregory D. Roach, Michael Maclennan and Charli Sargent

Sensors 2022, 22(18), 6723; https://doi.org/10.3390/s22186723 - 6 Sep 2022

Cited by 10 | Viewed by 4034

Abstract

Heart rate (HR) and HR variability (HRV) can be used to infer readiness to perform exercise in athletic populations. Advancements in the photoplethysmography technology of wearable devices such as WHOOP allow for the frequent and convenient measurement of HR and HRV, and therefore [...] Read more.

Heart rate (HR) and HR variability (HRV) can be used to infer readiness to perform exercise in athletic populations. Advancements in the photoplethysmography technology of wearable devices such as WHOOP allow for the frequent and convenient measurement of HR and HRV, and therefore enhanced application in athletes. However, it is important that the reliability of such technology is acceptable prior to its application in practical settings. Eleven elite male water polo players (age 28.8 ± 5.3 years [mean ± standard deviation]; height 190.3 ± 3.8 cm; body mass 95.0 ± 6.9 kg; international matches 117.9 ± 92.1) collected their HR and HRV daily via a WHOOP strap (WHOOP 3.0, CB Rank, Boston, MA, USA) over 16 weeks ahead of the 2021 Tokyo Olympic Games. The WHOOP strap quantified HR and HRV via wrist-based photoplethysmography during overnight sleep periods. The weekly (i.e., 7-day) coefficient of variation in lnRMSSD (lnRMSSD_CV) and HR (HR_CV) was calculated as a measure of day-to-day variability in lnRMSSD and HR, and presented as a mean of the entire recording period. The mean weekly lnRMSSD_CV and HR_CV over the 16-week period was 5.4 ± 0.7% (mean ± 95% confidence intervals) and 7.6 ± 1.3%, respectively. The day-to-day variability in WHOOP-derived lnRMSSD and HR is within or below the range of day-to-day variability in alternative lnRMSSD (~3–13%) and HR (~10–11%) assessment protocols, indicating that the assessment of HR and HRV by WHOOP does not introduce any more variability than that which is naturally present in these variables. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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15 pages, 4676 KiB

Open AccessArticle

Novel Method for Estimating Propulsive Force Generated by Swimmers’ Hands Using Inertial Measurement Units and Pressure Sensors

by Tomoya Kadi, Tomohito Wada, Kenzo Narita, Takaaki Tsunokawa, Hirotoshi Mankyu, Hiroyuki Tamaki and Futoshi Ogita

Sensors 2022, 22(17), 6695; https://doi.org/10.3390/s22176695 - 4 Sep 2022

Cited by 4 | Viewed by 2678

Abstract

Propulsive force is a determinant of swimming performance. Several methods have been proposed to estimate the propulsive force in human swimming; however, their practical use in coaching is limited. Herein, we propose a novel method for estimating the propulsive force generated by swimmers’ [...] Read more.

Propulsive force is a determinant of swimming performance. Several methods have been proposed to estimate the propulsive force in human swimming; however, their practical use in coaching is limited. Herein, we propose a novel method for estimating the propulsive force generated by swimmers’ hands using an inertial measurement unit (IMU) and pressure sensors. In Experiment 1, we use a hand model to examine the effect of a hand-mounted IMU on pressure around the hand model at several flow velocities and water flow directions. In Experiment 2, we compare the propulsive force estimated using the IMU and pressure sensors (

F_{IMU}

) via an underwater motion-capture system and pressure sensors (

F_{Mocap}

). Five swimmers had markers, pressure sensors, and IMUs attached to their hands and performed front crawl swimming for 25 m twice at each of nine different swimming speeds. The results show that the hand-mounted IMU affects the resultant force; however, the effect of the hand-mounted IMU varies with the flow direction. The mean values of

F_{Mocap}

and

F_{IMU}

are similar (19.59 ± 7.66 N and 19.36 ± 7.86 N, respectively; intraclass correlation coefficient_(2,1) = 0.966), and their waveforms are similar (coefficient of multiple correlation = 0.99). These results indicate that the IMU can estimate the same level of propulsive force as an underwater motion-capture system. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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16 pages, 3575 KiB

Open AccessArticle

Wearable-Based Stair Climb Power Estimation and Activity Classification

by Dimitrios J. Psaltos, Fahimeh Mamashli, Tomasz Adamusiak, Charmaine Demanuele, Mar Santamaria and Matthew D. Czech

Sensors 2022, 22(17), 6600; https://doi.org/10.3390/s22176600 - 1 Sep 2022

Cited by 2 | Viewed by 5062

Abstract

Stair climb power (SCP) is a clinical measure of leg muscular function assessed in-clinic via the Stair Climb Power Test (SCPT). This method is subject to human error and cannot provide continuous remote monitoring. Continuous monitoring using wearable sensors may provide a more [...] Read more.

Stair climb power (SCP) is a clinical measure of leg muscular function assessed in-clinic via the Stair Climb Power Test (SCPT). This method is subject to human error and cannot provide continuous remote monitoring. Continuous monitoring using wearable sensors may provide a more comprehensive assessment of lower-limb muscular function. In this work, we propose an algorithm to classify stair climbing periods and estimate SCP from a lower-back worn accelerometer, which strongly agrees with the clinical standard (r = 0.92, p < 0.001; ICC = 0.90, [0.82, 0.94]). Data were collected in-lab from healthy adults (n = 65) performing the four-step SCPT and a walking assessment while instrumented (accelerometer + gyroscope), which allowed us to investigate tradeoffs between sensor modalities. Using two classifiers, we were able to identify periods of stair ascent with >89% accuracy [sensitivity = >0.89, specificity = >0.90] using two ensemble machine learning algorithms, trained on accelerometer signal features. Minimal changes in model performances were observed using the gyroscope alone (±0–6% accuracy) versus the accelerometer model. While we observed a slight increase in accuracy when combining gyroscope and accelerometer (about +3–6% accuracy), this is tolerable to preserve battery life in the at-home environment. This work is impactful as it shows potential for an accelerometer-based at-home assessment of SCP. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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17 pages, 1768 KiB

Open AccessEditor’s ChoiceArticle

A Validation of Six Wearable Devices for Estimating Sleep, Heart Rate and Heart Rate Variability in Healthy Adults

by Dean J. Miller, Charli Sargent and Gregory D. Roach

Sensors 2022, 22(16), 6317; https://doi.org/10.3390/s22166317 - 22 Aug 2022

Cited by 91 | Viewed by 36012

Abstract

The primary aim of this study was to examine the validity of six commonly used wearable devices, i.e., Apple Watch S6, Garmin Forerunner 245 Music, Polar Vantage V, Oura Ring Generation 2, WHOOP 3.0 and Somfit, for assessing sleep. The secondary aim was [...] Read more.

The primary aim of this study was to examine the validity of six commonly used wearable devices, i.e., Apple Watch S6, Garmin Forerunner 245 Music, Polar Vantage V, Oura Ring Generation 2, WHOOP 3.0 and Somfit, for assessing sleep. The secondary aim was to examine the validity of the six devices for assessing heart rate and heart rate variability during, or just prior to, night-time sleep. Fifty-three adults (26 F, 27 M, aged 25.4 ± 5.9 years) spent a single night in a sleep laboratory with 9 h in bed (23:00–08:00 h). Participants were fitted with all six wearable devices—and with polysomnography and electrocardiography for gold-standard assessment of sleep and heart rate, respectively. Compared with polysomnography, agreement (and Cohen’s kappa) for two-state categorisation of sleep periods (as sleep or wake) was 88% (κ = 0.30) for Apple Watch; 89% (κ = 0.35) for Garmin; 87% (κ = 0.44) for Polar; 89% (κ = 0.51) for Oura; 86% (κ = 0.44) for WHOOP and 87% (κ = 0.48) for Somfit. Compared with polysomnography, agreement (and Cohen’s kappa) for multi-state categorisation of sleep periods (as a specific sleep stage or wake) was 53% (κ = 0.20) for Apple Watch; 50% (κ = 0.25) for Garmin; 51% (κ = 0.28) for Polar; 61% (κ = 0.43) for Oura; 60% (κ = 0.44) for WHOOP and 65% (κ = 0.52) for Somfit. Analyses regarding the two-state categorisation of sleep indicate that all six devices are valid for the field-based assessment of the timing and duration of sleep. However, analyses regarding the multi-state categorisation of sleep indicate that all six devices require improvement for the assessment of specific sleep stages. As the use of wearable devices that are valid for the assessment of sleep increases in the general community, so too does the potential to answer research questions that were previously impractical or impossible to address—in some way, we could consider that the whole world is becoming a sleep laboratory. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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16 pages, 5085 KiB

Open AccessArticle

Agreement of Sleep Measures—A Comparison between a Sleep Diary and Three Consumer Wearable Devices

by Kristina Klier and Matthias Wagner

Sensors 2022, 22(16), 6189; https://doi.org/10.3390/s22166189 - 18 Aug 2022

Cited by 7 | Viewed by 3025

Abstract

Nowadays, self-tracking and optimization are widely spread. As sleep is essential for well-being, health, and peak performance, the number of available consumer technologies to assess individual sleep behavior is increasing rapidly. However, little is known about the consumer wearables’ usability and reliability for [...] Read more.

Nowadays, self-tracking and optimization are widely spread. As sleep is essential for well-being, health, and peak performance, the number of available consumer technologies to assess individual sleep behavior is increasing rapidly. However, little is known about the consumer wearables’ usability and reliability for sleep tracking. Therefore, the aim of the present study was to compare the sleep measures of wearable devices with a standardized sleep diary in young healthy adults in free-living conditions. We tracked night sleep from 30 participants (19 females, 11 males; 24.3 ± 4.2 years old). Each wore three wearables and simultaneously assessed individual sleep patterns for four consecutive nights. Wearables and diaries correlated substantially regarding time in bed (Range CCC_Lin: 0.74–0.84) and total sleep time (Range CCC_Lin: 0.76–0.85). There was no sufficient agreement regarding the measures of sleep efficiency (Range CCC_Lin: 0.05–0.34) and sleep interruptions (Range CCC_Lin: −0.02–0.10). Finally, these results show wearables to be an easy-to-handle, time- and cost-efficient alternative to tracking sleep in healthy populations. Future research should develop and empirically test the usability of such consumer sleep technologies. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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13 pages, 2917 KiB

Open AccessArticle

Effects of a Long-Term Wearable Activity Tracker-Based Exercise Intervention on Cardiac Morphology and Function of Patients with Cystic Fibrosis

by Maria Anifanti, Stavros Giannakoulakos, Elpis Hatziagorou, Asterios Kampouras, John Tsanakas, Asterios Deligiannis and Evangelia Kouidi

Sensors 2022, 22(13), 4884; https://doi.org/10.3390/s22134884 - 28 Jun 2022

Cited by 2 | Viewed by 2421

Abstract

Several studies have shown that patients with cystic fibrosis (CF), even at a young age, have pulmonary and cardiac abnormalities. The main complications are cardiac right ventricular (RV) systolic and/or diastolic dysfunction and pulmonary hypertension, which affects their prognosis. Exercise training (ET) is [...] Read more.

Several studies have shown that patients with cystic fibrosis (CF), even at a young age, have pulmonary and cardiac abnormalities. The main complications are cardiac right ventricular (RV) systolic and/or diastolic dysfunction and pulmonary hypertension, which affects their prognosis. Exercise training (ET) is recommended in patients with CF as a therapeutic modality to improve physical fitness and health-related quality of life. However, questions remain regarding its optimal effective and safe dose and its effects on the patients’ cardiac function. The study aimed to provide a wearable activity tracker (WAT)-based ET to promote physical activity in CF patients and assess its effects on cardiac morphology and function. Forty-two stable CF individuals (aged 16.8 ± 3.6 years) were randomly assigned to either the intervention (Group A) or the control group (Group B). Group A participated in a 1-year WAT-based ET program three times per week. All patients underwent a 6-min walking test (6-MWT) and an echocardiographic assessment focused mainly on RV anatomy and function at the baseline and the end of the study. RV systolic function was evaluated by measuring the tricuspid annular plane systolic excursion (TAPSE), the systolic tricuspid annular velocity (TVS’), the RV free-wall longitudinal strain (RVFWSL), and the right ventricular four-chamber longitudinal strain (RV4CSL). RV diastolic function was assessed using early (TVE) and late (TVA) diastolic transtricuspid flow velocity and their ratio TVE/A. Pulmonary artery systolic pressure (PASP) was also estimated. In Group A after ET, the 6MWT distance improved by 20.6% (p < 0.05), TVA decreased by 17% (p < 0.05), and TVE/A increased by 13.2% (p < 0.05). Moreover, TAPSE, TVS’, RVFWSL, and RV4CSL increased by 8.3% (p < 0.05), 9.0% (p < 0.05), 13.7% (p < 0.05), and 26.7% (p < 0.05), respectively, while PASP decreased by 7.6% (p < 0.05). At the end of the study, there was a significant linear correlation between the number of steps and the PASP (r = −0.727, p < 0.01) as well as the indices of RV systolic function in Group A. In conclusion, WAT is a valuable tool for implementing an effective ET program in CF. Furthermore, ET has a positive effect on RV systolic and diastolic function. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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16 pages, 4512 KiB

Open AccessArticle

Accuracy and Precision of Wearable Devices for Real-Time Monitoring of Swimming Athletes

by Gloria Cosoli, Luca Antognoli, Valentina Veroli and Lorenzo Scalise

Sensors 2022, 22(13), 4726; https://doi.org/10.3390/s22134726 - 23 Jun 2022

Cited by 28 | Viewed by 5831

Abstract

Nowadays, the use of wearable devices is spreading in different fields of application, such as healthcare, digital health, and sports monitoring. In sport applications, the present trend is to continuously monitor the athletes’ physiological parameters during training or competitions to maximize performance and [...] Read more.

Nowadays, the use of wearable devices is spreading in different fields of application, such as healthcare, digital health, and sports monitoring. In sport applications, the present trend is to continuously monitor the athletes’ physiological parameters during training or competitions to maximize performance and support coaches. This paper aims to evaluate the performances in heart rate assessment, in terms of accuracy and precision, of both wrist-worn and chest-strap commercial devices used during swimming activity, considering a test population of 10 expert swimmers. Three devices were employed: Polar H10 cardiac belt, Polar Vantage V2, and Garmin Venu Sq smartwatches. The former was used as a reference device to validate the data measured by the two smartwatches. Tests were performed both in dry and wet conditions, considering walking/running on a treadmill and different swimming styles in water, respectively. The measurement accuracy and precision were evaluated through standard methods, i.e., Bland–Altman plot, analysis of deviations, and Pearson’s correlation coefficient. Results show that both precision and accuracy worsen during swimming activity (with an absolute increase of the measurement deviation in the range of 13–56 bpm for mean value and 49–52 bpm for standard deviation), proving how water and arms movement act as relevant interference inputs. Moreover, it was found that wearable performance decreases when activity intensity increases, highlighting the need for specific research for wearable applications in water, with a particular focus on swimming-related sports activities. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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11 pages, 562 KiB

Open AccessArticle

On-Court Activity and Game-Related Statistics during Scoring Streaks in Basketball: Applied Use of Accelerometers

by Jodie A. Palmer, Rodrigo Bini, Daniel Wundersitz and Michael Kingsley

Sensors 2022, 22(11), 4059; https://doi.org/10.3390/s22114059 - 27 May 2022

Cited by 8 | Viewed by 2086

Abstract

The aim of this observational study was to determine if on-court activity and match statistics differed between periods of scoring streaks and regular play in basketball. Thirty-seven basketballers including professional women, semi-professional women and semi-professional men wore accelerometers during competitive matches throughout a [...] Read more.

The aim of this observational study was to determine if on-court activity and match statistics differed between periods of scoring streaks and regular play in basketball. Thirty-seven basketballers including professional women, semi-professional women and semi-professional men wore accelerometers during competitive matches throughout a season. Accelerometry-derived live-time individual on-court exercise intensity and team game-related statistics were compared between scoring streaks (periods of play where the teams participating in the study scored at least three times in a row), streaks against (periods of play where the opposition teams scored at least three times in a row) and regular play. Few differences existed in the average exercise intensity between streak types. During streaks against, there was a 5–15% lower proportion of 2-point attempts, 0.8–1.3 fewer defensive rebounds per minute and 0.3–1.6 fewer shot attempts per minute compared to regular play and scoring streaks, and there were 0.3 fewer offensive rebounds per minute compared to regular play. During scoring streaks, there were 0.5 more defensive rebounds per minute, 1.3 more shot attempts per minute, a 43% greater shooting percentage and a 10% lower proportion of 3-point attempts compared to regular play. To reduce the chances of streaks against, teams should focus on facilitating 2-point shot attempts and consider implementing a 3:1 ratio of 2-point to 3-point attempts to maximize scoring success, and they should focus on winning rebounds to facilitate more shot attempts. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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12 pages, 2968 KiB

Open AccessArticle

Validation of Running Gait Event Detection Algorithms in a Semi-Uncontrolled Environment

by Seth R. Donahue and Michael E. Hahn

Sensors 2022, 22(9), 3452; https://doi.org/10.3390/s22093452 - 30 Apr 2022

Cited by 4 | Viewed by 2377

Abstract

The development of lightweight portable sensors and algorithms for the identification of gait events at steady-state running speeds can be translated into the real-world environment. However, the output of these algorithms needs to be validated. The purpose of this study was to validate [...] Read more.

The development of lightweight portable sensors and algorithms for the identification of gait events at steady-state running speeds can be translated into the real-world environment. However, the output of these algorithms needs to be validated. The purpose of this study was to validate the identification of running gait events using data from Inertial Measurement Units (IMUs) in a semi-uncontrolled environment. Fifteen healthy runners were recruited for this study, with varied running experience and age. Force-sensing insoles measured normal foot-shoe forces and provided a standard for identification of gait events. Three IMUs were mounted to the participant, two bilaterally on the dorsal aspect of the foot and one clipped to the back of each participant’s waistband, approximating their sacrum. The identification of gait events from the foot-mounted IMU was more accurate than from the sacral-mounted IMU. At running speeds <3.57 m s⁻¹, the sacral-mounted IMU identified contact duration as well as the foot-mounted IMU. However, at speeds >3.57 m s⁻¹, the sacral-mounted IMU overestimated foot contact duration. This study demonstrates that at controlled paces over level ground, we can identify gait events and measure contact time across a range of running skill levels. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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17 pages, 2061 KiB

Open AccessArticle

Impact of Gender and Feature Set on Machine-Learning-Based Prediction of Lower-Limb Overuse Injuries Using a Single Trunk-Mounted Accelerometer

by Sieglinde Bogaert, Jesse Davis, Sam Van Rossom and Benedicte Vanwanseele

Sensors 2022, 22(8), 2860; https://doi.org/10.3390/s22082860 - 8 Apr 2022

Cited by 4 | Viewed by 2125

Abstract

Even though practicing sports has great health benefits, it also entails a risk of developing overuse injuries, which can elicit a negative impact on physical, mental, and financial health. Being able to predict the risk of an overuse injury arising is of widespread [...] Read more.

Even though practicing sports has great health benefits, it also entails a risk of developing overuse injuries, which can elicit a negative impact on physical, mental, and financial health. Being able to predict the risk of an overuse injury arising is of widespread interest because this may play a vital role in preventing its occurrence. In this paper, we present a machine learning model trained to predict the occurrence of a lower-limb overuse injury (LLOI). This model was trained and evaluated using data from a three-dimensional accelerometer on the lower back, collected during a Cooper test performed by 161 first-year undergraduate students of a movement science program. In this study, gender-specific models performed better than mixed-gender models. The estimated area under the receiving operating characteristic curve of the best-performing male- and female-specific models, trained according to the presented approach, was, respectively, 0.615 and 0.645. In addition, the best-performing models were achieved by combining statistical and sports-specific features. Overall, the results demonstrated that a machine learning injury prediction model is a promising, yet challenging approach. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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9 pages, 2295 KiB

Open AccessCommunication

An Experimental Feasibility Study Evaluating the Adequacy of a Sportswear-Type Wearable for Recording Exercise Intensity

by Yoshihiro Marutani, Shoji Konda, Issei Ogasawara, Keita Yamasaki, Teruki Yokoyama, Etsuko Maeshima and Ken Nakata

Sensors 2022, 22(7), 2577; https://doi.org/10.3390/s22072577 - 28 Mar 2022

Cited by 6 | Viewed by 3099

Abstract

Sportswear-type wearables with integrated inertial sensors and electrocardiogram (ECG) electrodes have been commercially developed. We evaluated the feasibility of using a sportswear-type wearable with integrated inertial sensors and electrocardiogram (ECG) electrodes for evaluating exercise intensity within a controlled laboratory setting. Six male college [...] Read more.

Sportswear-type wearables with integrated inertial sensors and electrocardiogram (ECG) electrodes have been commercially developed. We evaluated the feasibility of using a sportswear-type wearable with integrated inertial sensors and electrocardiogram (ECG) electrodes for evaluating exercise intensity within a controlled laboratory setting. Six male college athletes were asked to wear a sportswear-type wearable while performing a treadmill test that reached up to 20 km/h. The magnitude of the filtered tri-axial acceleration signal, recorded by the inertial sensor, was used to calculate the acceleration index. The R-R intervals of the ECG were used to determine heart rate; the external validity of the heart rate was then evaluated according to oxygen uptake, which is the gold standard for physiological exercise intensity. Single regression analysis between treadmill speed and the acceleration index in each participant showed that the slope of the regression line was significantly greater than zero with a high coefficient of determination (walking, 0.95; jogging, 0.96; running, 0.90). Another single regression analysis between heart rate and oxygen uptake showed that the slope of the regression line was significantly greater than zero, with a high coefficient of determination (0.96). Together, these results indicate that the sportswear-type wearable evaluated in this study is a feasible technology for evaluating physical and physiological exercise intensity across a wide range of physical activities and sport performances. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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13 pages, 1522 KiB

Open AccessArticle

A Novel Physical Fatigue Assessment Method Utilizing Heart Rate Variability and Pulse Arrival Time towards Personalized Feedback with Wearable Sensors

by Ardo Allik, Kristjan Pilt, Moonika Viigimäe, Ivo Fridolin and Gert Jervan

Sensors 2022, 22(4), 1680; https://doi.org/10.3390/s22041680 - 21 Feb 2022

Cited by 2 | Viewed by 3411

Abstract

This paper proposes a novel method for physical fatigue assessment that can be applied in wearable systems, by utilizing a set of real-time measurable cardiovascular parameters. Daylength measurements, including a morning test set, physical exercise during the day, and an afternoon test set [...] Read more.

This paper proposes a novel method for physical fatigue assessment that can be applied in wearable systems, by utilizing a set of real-time measurable cardiovascular parameters. Daylength measurements, including a morning test set, physical exercise during the day, and an afternoon test set were conducted on 16 healthy subjects (8 female and 8 male). To analyze cardiovascular parameters for physical fatigue assessment, electrocardiography, pulse wave and blood pressure were measured during the test sets. The fatigue assessment questionnaire score, reaction time, countermovement jump height and hand grip strength were also measured and used as reference parameters. This study demonstrates that (i) the compiled test battery can selectively assess the rested vs. physically-fatigued states; (ii) the obtained linear support-vector machine, trained using the heart rate variability based parameter (F-score 0.842, accuracy 0.813) and pulse arrival time based parameter (F-score 0.875, accuracy 0.875) shows a promising ability to classify between the physically mildly fatigued and significantly fatigued states. Despite the somewhat limited study group size, the results of the study are unique and provide a significant advancement on the existing physical fatigue assessment methods towards a personalized and continuous real-time fatigue monitoring system with wearable sensors. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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27 pages, 3513 KiB

Open AccessArticle

An End-to-End Deep Learning Pipeline for Football Activity Recognition Based on Wearable Acceleration Sensors

by Rafael Cuperman, Kaspar M. B. Jansen and Michał G. Ciszewski

Sensors 2022, 22(4), 1347; https://doi.org/10.3390/s22041347 - 10 Feb 2022

Cited by 19 | Viewed by 4059

Abstract

Action statistics in sports, such as the number of sprints and jumps, along with the details of the corresponding locomotor actions, are of high interest to coaches and players, as well as medical staff. Current video-based systems have the disadvantage that they are [...] Read more.

Action statistics in sports, such as the number of sprints and jumps, along with the details of the corresponding locomotor actions, are of high interest to coaches and players, as well as medical staff. Current video-based systems have the disadvantage that they are costly and not easily transportable to new locations. In this study, we investigated the possibility to extract these statistics from acceleration sensor data generated by a previously developed sensor garment. We used deep learning-based models to recognize five football-related activities (jogging, sprinting, passing, shooting and jumping) in an accurate, robust, and fast manner. A combination of convolutional (CNN) layers followed by recurrent (bidirectional) LSTM layers achieved up to 98.3% of accuracy. Our results showed that deep learning models performed better in evaluation time and prediction accuracy than traditional machine learning algorithms. In addition to an increase in accuracy, the proposed deep learning architecture showed to be 2.7 to 3.4 times faster in evaluation time than traditional machine learning methods. This demonstrated that deep learning models are accurate as well as time-efficient and are thus highly suitable for cost-effective, fast, and accurate human activity recognition tasks. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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19 pages, 5057 KiB

Open AccessArticle

Reliability and Validity of an Inertial Measurement System to Quantify Lower Extremity Joint Angle in Functional Movements

by Zhenyu Shuai, Anqi Dong, Haoyang Liu and Yixiong Cui

Sensors 2022, 22(3), 863; https://doi.org/10.3390/s22030863 - 23 Jan 2022

Cited by 19 | Viewed by 4411

Abstract

The purpose of this research was to determine if the commercially available Perception Neuron motion capture system was valid and reliable in clinically relevant lower limb functional tasks. Twenty healthy participants performed two sessions on different days: gait, squat, single-leg squat, side lunge, [...] Read more.

The purpose of this research was to determine if the commercially available Perception Neuron motion capture system was valid and reliable in clinically relevant lower limb functional tasks. Twenty healthy participants performed two sessions on different days: gait, squat, single-leg squat, side lunge, forward lunge, and counter-movement jump. Seven IMUs and an OptiTrack system were used to record the three-dimensional joint kinematics of the lower extremity. To evaluate the performance, the multiple correlation coefficient (CMC) and the root mean square error (RMSE) of the waveforms as well as the difference and intraclass correlation coefficient (ICC) of discrete parameters were calculated. In all tasks, the CMC revealed fair to excellent waveform similarity (0.47–0.99) and the RMSE was between 3.57° and 13.14°. The difference between discrete parameters was lower than 14.54°. The repeatability analysis of waveforms showed that the CMC was between 0.54 and 0.95 and the RMSE was less than 5° in the frontal and transverse planes. The ICC of all joint angles in the IMU was general to excellent (0.57–1). Our findings showed that the IMU system might be utilized to evaluate lower extremity 3D joint kinematics in functional motions. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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22 pages, 1279 KiB

Open AccessArticle

A Music Playback Algorithm Based on Residual-Inception Blocks for Music Emotion Classification and Physiological Information

by Yi-Jr Liao, Wei-Chun Wang, Shanq-Jang Ruan, Yu-Hao Lee and Shih-Ching Chen

Sensors 2022, 22(3), 777; https://doi.org/10.3390/s22030777 - 20 Jan 2022

Cited by 7 | Viewed by 2774

Abstract

Music can generate a positive effect in runners’ performance and motivation. However, the practical implementation of music intervention during exercise is mostly absent from the literature. Therefore, this paper designs a playback sequence system for joggers by considering music emotion and physiological signals. [...] Read more.

Music can generate a positive effect in runners’ performance and motivation. However, the practical implementation of music intervention during exercise is mostly absent from the literature. Therefore, this paper designs a playback sequence system for joggers by considering music emotion and physiological signals. This playback sequence is implemented by a music selection module that combines artificial intelligence techniques with physiological data and emotional music. In order to make the system operate for a long time, this paper improves the model and selection music module to achieve lower energy consumption. The proposed model obtains fewer FLOPs and parameters by using logarithm scaled Mel-spectrogram as input features. The accuracy, computational complexity, trainable parameters, and inference time are evaluated on the Bi-modal, 4Q emotion, and Soundtrack datasets. The experimental results show that the proposed model is better than that of Sarkar et al. and achieves competitive performance on Bi-modal (84.91%), 4Q emotion (92.04%), and Soundtrack (87.24%) datasets. More specifically, the proposed model reduces the computational complexity and inference time while maintaining the classification accuracy, compared to other models. Moreover, the size of the proposed model for network training is small, which can be applied to mobiles and other devices with limited computing resources. This study designed the overall playback sequence system by considering the relationship between music emotion and physiological situation during exercise. The playback sequence system can be adopted directly during exercise to improve users’ exercise efficiency. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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15 pages, 943 KiB

Open AccessArticle

How Long Should GPS Recording Lengths Be to Capture the Community Mobility of An Older Clinical Population? A Parkinson’s Example

by Lynn Zhu, Patrick Boissy, Christian Duval, Guangyong Zou, Mandar Jog, Manuel Montero-Odasso and Mark Speechley

Sensors 2022, 22(2), 563; https://doi.org/10.3390/s22020563 - 12 Jan 2022

Cited by 3 | Viewed by 2154

Abstract

Wearable global position system (GPS) technology can help those working with older populations and people living with movement disorders monitor and maintain their mobility level. Health research using GPS often employs inconsistent recording lengths due to the lack of a standard minimum GPS [...] Read more.

Wearable global position system (GPS) technology can help those working with older populations and people living with movement disorders monitor and maintain their mobility level. Health research using GPS often employs inconsistent recording lengths due to the lack of a standard minimum GPS recording length for a clinical context. Our work aimed to recommend a GPS recording length for an older clinical population. Over 14 days, 70 older adults with Parkinson’s disease wore the wireless inertial motion unit with GPS (WIMU-GPS) during waking hours to capture daily “time outside”, “trip count”, “hotspots count” and “area size travelled”. The longest recording length accounting for weekend and weekdays was ≥7 days of ≥800 daily minutes of data (14 participants with 156, 483.9 min recorded). We compared the error rate generated when using data based on recording lengths shorter than this sample. The smallest percentage errors were observed across all outcomes, except “hotspots count”, with daily recordings ≥500 min (8.3 h). Eight recording days will capture mobility variability throughout days of the week. This study adds empirical evidence to the sensor literature on the required minimum duration of GPS recording. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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14 pages, 2656 KiB

Open AccessArticle

Manual Annotation of Time in Bed Using Free-Living Recordings of Accelerometry Data

by Esben Lykke Skovgaard, Jesper Pedersen, Niels Christian Møller, Anders Grøntved and Jan Christian Brønd

Sensors 2021, 21(24), 8442; https://doi.org/10.3390/s21248442 - 17 Dec 2021

Cited by 3 | Viewed by 2878

Abstract

With the emergence of machine learning for the classification of sleep and other human behaviors from accelerometer data, the need for correctly annotated data is higher than ever. We present and evaluate a novel method for the manual annotation of in-bed periods in [...] Read more.

With the emergence of machine learning for the classification of sleep and other human behaviors from accelerometer data, the need for correctly annotated data is higher than ever. We present and evaluate a novel method for the manual annotation of in-bed periods in accelerometer data using the open-source software Audacity^®, and we compare the method to the EEG-based sleep monitoring device Zmachine^® Insight+ and self-reported sleep diaries. For evaluating the manual annotation method, we calculated the inter- and intra-rater agreement and agreement with Zmachine and sleep diaries using interclass correlation coefficients and Bland–Altman analysis. Our results showed excellent inter- and intra-rater agreement and excellent agreement with Zmachine and sleep diaries. The Bland–Altman limits of agreement were generally around ±30 min for the comparison between the manual annotation and the Zmachine timestamps for the in-bed period. Moreover, the mean bias was minuscule. We conclude that the manual annotation method presented is a viable option for annotating in-bed periods in accelerometer data, which will further qualify datasets without labeling or sleep records. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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13 pages, 2495 KiB

Open AccessArticle

Reliability and Validity of Running Cadence and Stance Time Derived from Instrumented Wireless Earbuds

by Anouk Nijs, Peter J. Beek and Melvyn Roerdink

Sensors 2021, 21(23), 7995; https://doi.org/10.3390/s21237995 - 30 Nov 2021

Cited by 6 | Viewed by 3386

Abstract

Instrumented earbuds equipped with accelerometers were developed in response to limitations of currently used running wearables regarding sensor location and feedback delivery. The aim of this study was to assess test–retest reliability, face validity and concurrent validity for cadence and stance time in [...] Read more.

Instrumented earbuds equipped with accelerometers were developed in response to limitations of currently used running wearables regarding sensor location and feedback delivery. The aim of this study was to assess test–retest reliability, face validity and concurrent validity for cadence and stance time in running. Participants wore an instrumented earbud (new method) while running on a treadmill with embedded force-plates (well-established method). They ran at a range of running speeds and performed several instructed head movements while running at a comfortable speed. Cadence and stance time were derived from raw earbud and force-plate data and compared within and between both methods using t-tests, ICC and Bland–Altman analysis. Test–retest reliability was good-to-excellent for both methods. Face validity was demonstrated for both methods, with cadence and stance time varying with speed in to-be-expected directions. Between-methods agreement for cadence was excellent for all speeds and instructed head movements. For stance time, agreement was good-to-excellent for all conditions, except while running at 13 km/h and shaking the head. Overall, the measurement of cadence and stance time using an accelerometer embedded in a wireless earbud showed good test–retest reliability, face validity and concurrent validity, indicating that instrumented earbuds may provide a promising alternative to currently used wearable systems. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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16 pages, 7052 KiB

Open AccessArticle

Experimental Validation of Real-Time Ski Jumping Tracking System Based on Wearable Sensors

by Johannes Link, Sébastien Guillaume and Bjoern M. Eskofier

Sensors 2021, 21(23), 7780; https://doi.org/10.3390/s21237780 - 23 Nov 2021

Cited by 6 | Viewed by 2934

Abstract

For sports scientists and coaches, its crucial to have reliable tracking systems to improve athletes. Therefore, this study aimed to examine the validity of a wearable real-time tracking system (WRRTS) for the quantification of ski jumping. The tracking system consists of wearable trackers [...] Read more.

For sports scientists and coaches, its crucial to have reliable tracking systems to improve athletes. Therefore, this study aimed to examine the validity of a wearable real-time tracking system (WRRTS) for the quantification of ski jumping. The tracking system consists of wearable trackers attached to the ski bindings of the athletes and fixed antennas next to the jumping hill. To determine the accuracy and precision of the WRRTS, four athletes of the German A or B National Team performed 35 measured ski jumps. The WRRTS was used to measure the 3D positions and ski angles during the jump. The measurements are compared with camera measurements for the in-flight parameters and the official video distance for the jumping distance to assess their accuracy. We statistically evaluated the different methods using Bland–Altman plots. We thereby find a mean absolute error of

0.46

m

for the jumping distance,

0.12

m

for the in-flight positions, and

0.8

°, and

3.4

° for the camera projected pitch and V-style opening angle, respectively. We show the validity of the presented WRRTS to measure the investigated parameters. Thus, the system can be used as a tracking system during training and competitions for coaches and sports scientists. The real-time feature of the tracking system enables usage during live TV broadcasting. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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9 pages, 2502 KiB

Open AccessCommunication

Reliability and Validity of the SHFT Running Power Meter

by Jesper Emil Linkis, Thomas Christian Bonne, Jacob Bejder, Esben Krogh Rasmussen, Andreas Breenfeldt Andersen and Nikolai Baastrup Nordsborg

Sensors 2021, 21(22), 7516; https://doi.org/10.3390/s21227516 - 12 Nov 2021

Cited by 2 | Viewed by 2421

Abstract

The SHFT device is a novel running wearable consisting of two pods connected to your smartphone issuing several running metrics based on accelerometer and gyroscope technology. The purpose of this study was to investigate the reliability and validity of the power output (PO) [...] Read more.

The SHFT device is a novel running wearable consisting of two pods connected to your smartphone issuing several running metrics based on accelerometer and gyroscope technology. The purpose of this study was to investigate the reliability and validity of the power output (PO) metric produced by the SHFT device. To assess reliability, 12 men ran on an outdoor track at 10.5 km·h⁻¹ and 12 km·h⁻¹ on two consecutive days. To assess validity, oxygen uptake (VO₂) and SHFT data from eight men and seven women were collected during incremental submaximal running tests on an indoor treadmill on one to four separate days (34 tests in total). SHFT reliability on the outdoor track was strong with coefficients of variance (CV) of 1.8% and 2.4% for 10.5 and 12 km·h⁻¹, respectively. We observed a very strong linear relationship between PO and VO₂ (r² = 0.54) within subjects, and a very strong linear relationship within each subject within each treadmill test (r² = 0.80). We conclude that SHFT provides a reliable running power estimate and that a very strong relationship between SHFT-Power and metabolic rate exists, which places SHFT as one of the leading commercially available running power meters. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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13 pages, 2479 KiB

Open AccessArticle

The Use of a Single Trunk-Mounted Accelerometer to Detect Changes in Center of Mass Motion Linked to Lower-Leg Overuse Injuries: A Prospective Study

by Gerard Aristizábal Pla, Enzo Hollville, Kurt Schütte and Benedicte Vanwanseele

Sensors 2021, 21(21), 7385; https://doi.org/10.3390/s21217385 - 6 Nov 2021

Cited by 7 | Viewed by 3380

Abstract

Movement dynamics during running was previously characterized using a trunk-mounted accelerometer, and were associated with a history of overuse injuries. However, it remains unknown if these measures are also linked to the development of overuse injuries. The aim of this study was therefore [...] Read more.

Movement dynamics during running was previously characterized using a trunk-mounted accelerometer, and were associated with a history of overuse injuries. However, it remains unknown if these measures are also linked to the development of overuse injuries. The aim of this study was therefore to determine how movement dynamics alter in response to fatigue, and the possible link with developing lower-leg overuse injuries during a six-month follow-up period. Two hundred and eight movement science university students completed a 12-min all-out run while wearing a trunk-mounted accelerometer. Dynamic stability, dynamic loading and spatiotemporal measures were extracted from the accelerometer. Participants sustaining an injury within the 6-month period demonstrated significantly higher RMS ratio values in the vertical direction and lower RMS ratio values in the anteroposterior direction, and lower impact acceleration values in the anteroposterior direction in an unfatigued state compared to the uninjured group. They also demonstrated an increase in dynamic loading in the horizontal plane during the run. In addition, with running fatigue both groups exhibited changes in dynamic stability and loading measures. These results show the potential of using a single trunk-mounted accelerometer to detect changes in movement dynamics that are linked to lower-leg overuse injuries. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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12 pages, 617 KiB

Open AccessArticle

Validation of the Apple Watch for Estimating Moderate-to-Vigorous Physical Activity and Activity Energy Expenditure in School-Aged Children

by Sunku Kwon, Youngwon Kim, Yang Bai, Ryan D. Burns, Timothy A. Brusseau and Wonwoo Byun

Sensors 2021, 21(19), 6413; https://doi.org/10.3390/s21196413 - 25 Sep 2021

Cited by 11 | Viewed by 4650

Abstract

The Apple Watch is one of the most popular wearable devices designed to monitor physical activity (PA). However, it is currently unknown whether the Apple Watch accurately estimates children’s free-living PA. Therefore, this study assessed the concurrent validity of the Apple Watch 3 [...] Read more.

The Apple Watch is one of the most popular wearable devices designed to monitor physical activity (PA). However, it is currently unknown whether the Apple Watch accurately estimates children’s free-living PA. Therefore, this study assessed the concurrent validity of the Apple Watch 3 in estimating moderate-to-vigorous physical activity (MVPA) time and active energy expenditure (AEE) for school-aged children under a simulated and a free-living condition. Twenty elementary school students (Girls: 45%, age: 9.7 ± 2.0 years) wore an Apple Watch 3 device on their wrist and performed prescribed free-living activities in a lab setting. A subgroup of participants (N = 5) wore the Apple Watch for seven consecutive days in order to assess the validity in free-living condition. The K5 indirect calorimetry (K5) and GT3X+ were used as the criterion measure under simulated free-living and free-living conditions, respectively. Mean absolute percent errors (MAPE) and Bland-Altman (BA) plots were conducted to assess the validity of the Apple Watch 3 compared to those from the criterion measures. Equivalence testing determined the statistical equivalence between the Apple Watch and K5 for MVPA time and AEE. The Apple Watch provided comparable estimates for MVPA time (mean bias: 0.3 min, p = 0.91, MAPE: 1%) and for AEE (mean bias: 3.8 kcal min, p = 0.75, MAPE: 4%) during the simulated free-living condition. The BA plots indicated no systematic bias for the agreement in MVPA and AEE estimates between the K5 and Apple Watch 3. However, the Apple Watch had a relatively large variability in estimating AEE in children. The Apple Watch was statistically equivalent to the K5 within ±17.7% and ±20.8% for MVPA time and AEE estimates, respectively. Our findings suggest that the Apple Watch 3 has the potential to be used as a PA assessment tool to estimate MVPA in school-aged children. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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14 pages, 2415 KiB

Open AccessArticle

Laboratory Validation of Instrumented Mouthguard for Use in Sport

by Danyon Stitt, Nick Draper, Keith Alexander and Natalia Kabaliuk

Sensors 2021, 21(18), 6028; https://doi.org/10.3390/s21186028 - 9 Sep 2021

Cited by 9 | Viewed by 4082

Abstract

Concussion is an inherent risk of participating in contact, combat, or collision sports, within which head impacts are numerous. Kinematic parameters such as peak linear and rotational acceleration represent primary measures of concussive head impacts. The ability to accurately measure and categorise such [...] Read more.

Concussion is an inherent risk of participating in contact, combat, or collision sports, within which head impacts are numerous. Kinematic parameters such as peak linear and rotational acceleration represent primary measures of concussive head impacts. The ability to accurately measure and categorise such impact parameters in real time is important in health and sports performance contexts. The purpose of this study was to assess the accuracy of the latest HitIQ Nexus A9 instrumented mouthguard (HitIQ Pty. Ltd. Melbourne Australia) against reference sensors in an aluminium headform. The headform underwent drop testing at various impact intensities across the NOCSAE-defined impact locations, comparing the peak linear and rotational acceleration (PLA and PRA) as well as the shapes of the acceleration time-series traces for each impact. Mouthguard PLA and PRA measurements strongly correlated with (R² = 0.996 and 0.994 respectively), and strongly agreed with (LCCC = 0.997) the reference sensors. The root mean square error between the measurement devices was 1 ± 0.6g for linear acceleration and 47.4 ± 35 rad/s² for rotational acceleration. A Bland–Altman analysis found a systematic bias of 1% for PRA, with no significant bias for PLA. The instrumented mouthguard displayed high accuracy when measuring head impact kinematics in a laboratory setting. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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19 pages, 15008 KiB

Open AccessArticle

Ultra-Wideband Indoor Positioning and IMU-Based Activity Recognition for Ice Hockey Analytics

by Robbe Vleugels, Ben Van Herbruggen, Jaron Fontaine and Eli De Poorter

Sensors 2021, 21(14), 4650; https://doi.org/10.3390/s21144650 - 7 Jul 2021

Cited by 31 | Viewed by 6918

Abstract

Currently, gathering statistics and information for ice hockey training purposes mostly happens by hand, whereas the automated systems that do exist are expensive and difficult to set up. To remedy this, in this paper, we propose and analyse a wearable system that combines [...] Read more.

Currently, gathering statistics and information for ice hockey training purposes mostly happens by hand, whereas the automated systems that do exist are expensive and difficult to set up. To remedy this, in this paper, we propose and analyse a wearable system that combines player localisation and activity classification to automatically gather information. A stick-worn inertial measurement unit was used to capture acceleration and rotation data from six ice hockey activities. A convolutional neural network was able to distinguish the six activities from an unseen player with a 76% accuracy at a sample frequency of 100 Hz. Using unseen data from players used to train the model, a 99% accuracy was reached. With a peak detection algorithm, activities could be automatically detected and extracted from a complete measurement for classification. Additionally, the feasibility of a time difference of arrival based ultra-wideband system operating at a 25 Hz update rate was determined. We concluded that the system, when the data were filtered and smoothed, provided acceptable accuracy for use in ice hockey. Combining both, it was possible to gather useful information about a wide range of interesting performance measures. This shows that our proposed system is a suitable solution for the analysis of ice hockey. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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18 pages, 1178 KiB

Open AccessArticle

Tactowel: A Subtle Sports Performance Display for Giving Real-Time Performance Feedback in Tennis

by Hayati Havlucu, Aykut Coşkun and Oğuzhan Özcan

Sensors 2021, 21(13), 4594; https://doi.org/10.3390/s21134594 - 5 Jul 2021

Cited by 2 | Viewed by 2901

Abstract

Sports technology enhances athletes’ performance by providing feedback. However, interaction techniques of current devices may overwhelm athletes with excessive information or distract them from their performance. Despite previous research, design knowledge on how to interact with these devices to prevent such occasions are [...] Read more.

Sports technology enhances athletes’ performance by providing feedback. However, interaction techniques of current devices may overwhelm athletes with excessive information or distract them from their performance. Despite previous research, design knowledge on how to interact with these devices to prevent such occasions are scarce. To address this gap, we introduce subtle displays as real-time sports performance feedback output devices that unobtrusively present low-resolution information. In this paper, we conceptualize and apply subtle displays to tennis by designing Tactowel, a texture changing sports towel. We evaluate Tactowel through a remote user study with 8 professional tennis players, in which they experience, compare and discuss Tactowel. Our results suggest subtle displays could prevent overwhelming and distracting athletes through three distinct design strategies: (1) Restricting the use excluding duration of performance, (2) using the available routines and interactions, and (3) giving an overall abstraction through tangible interaction. We discuss these results to present design implications and future considerations for designing subtle displays. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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17 pages, 526 KiB

Open AccessArticle

Exploring the Use of Mobile and Wearable Technology among University Student Athletes in Lebanon: A Cross-Sectional Study

by Marco Bardus, Cecile Borgi, Marwa El-Harakeh, Tarek Gherbal, Samer Kharroubi and Elie-Jacques Fares

Sensors 2021, 21(13), 4472; https://doi.org/10.3390/s21134472 - 30 Jun 2021

Cited by 9 | Viewed by 6415

Abstract

The markets of commercial wearables and health and fitness apps are constantly growing globally, especially among young adults and athletes, to track physical activity, energy expenditure and health. Despite their wide availability, evidence on use comes predominantly from the United States or Global [...] Read more.

The markets of commercial wearables and health and fitness apps are constantly growing globally, especially among young adults and athletes, to track physical activity, energy expenditure and health. Despite their wide availability, evidence on use comes predominantly from the United States or Global North, with none targeting college student-athletes in low- and middle-income countries. This study was aimed to explore the use of these technologies among student-athletes at the American University of Beirut (AUB). We conducted a cross-sectional survey of 482 participants (average age 20 years) enrolled in 24 teams during Fall 2018; 230 students successfully completed the web-based survey, and 200 provided valid data. Fifty-three (26.5%) have owned a fitness tracker, mostly for self-monitoring. The most popular were Fitbit, Apple Watch, and Garmin. Similarly, 82 students (40%) used apps, primarily MyFitnessPal, Apple Health, and Samsung Health. Nevertheless, many participants discontinued use due to loss of interest or technical issues (breaking, usability, obsolescence, or lack of engagement). Wearable devices were considered superior to mobile phones alone as physical activity monitors. However, forming regular habits made self-monitoring via technology irrelevant. Further research is needed to better understand what motivates continuous use among student-athletes, who could use trackers to improve athletic performance and overall health. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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13 pages, 12107 KiB

Open AccessArticle

Noninvasive Estimation of Hydration Status in Athletes Using Wearable Sensors and a Data-Driven Approach Based on Orthostatic Changes

by Fahad Kamran, Victor C. Le, Adam Frischknecht, Jenna Wiens and Kathleen H. Sienko

Sensors 2021, 21(13), 4469; https://doi.org/10.3390/s21134469 - 29 Jun 2021

Cited by 4 | Viewed by 3877

Abstract

Dehydration beyond 2% bodyweight loss should be monitored to reduce the risk of heat-related injuries during exercise. However, assessments of hydration in athletic settings can be limited in their accuracy and accessibility. In this study, we sought to develop a data-driven noninvasive approach [...] Read more.

Dehydration beyond 2% bodyweight loss should be monitored to reduce the risk of heat-related injuries during exercise. However, assessments of hydration in athletic settings can be limited in their accuracy and accessibility. In this study, we sought to develop a data-driven noninvasive approach to measure hydration status, leveraging wearable sensors and normal orthostatic movements. Twenty participants (10 males, 25.0 ± 6.6 years; 10 females, 27.8 ± 4.3 years) completed two exercise sessions in a heated environment: one session was completed without fluid replacement. Before and after exercise, participants performed 12 postural movements that varied in length (up to 2 min). Logistic regression models were trained to estimate dehydration status given their heart rate responses to these postural movements. The area under the receiver operating characteristic curve (AUROC) was used to parameterize the model’s discriminative ability. Models achieved an AUROC of 0.79 (IQR: 0.75, 0.91) when discriminating 2% bodyweight loss. The AUROC for the longer supine-to-stand postural movements and shorter toe-touches were similar (0.89, IQR: 0.89, 1.00). Shorter orthostatic tests achieved similar accuracy to clinical tests. The findings suggest that data from wearable sensors can be used to accurately estimate mild dehydration in athletes. In practice, this method may provide an additional measurement for early intervention of severe dehydration. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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14 pages, 1270 KiB

Open AccessArticle

How Are Sports-Trackers Used by Runners? Running-Related Data, Personal Goals, and Self-Tracking in Running

by Armağan Karahanoğlu, Rúben Gouveia, Jasper Reenalda and Geke Ludden

Sensors 2021, 21(11), 3687; https://doi.org/10.3390/s21113687 - 26 May 2021

Cited by 21 | Viewed by 6939

Abstract

The purpose of this research is to explore the roles that sports trackers and running-related data play in runners’ personal goal achievement. A two-week diary study and semi-structured interviews were conducted with 22 runners to explore how runners engage with their running-related data [...] Read more.

The purpose of this research is to explore the roles that sports trackers and running-related data play in runners’ personal goal achievement. A two-week diary study and semi-structured interviews were conducted with 22 runners to explore how runners engage with their running-related data to set and achieve their running goals. We found that participants pursued and transitioned between different running goals as their needs, abilities, and surrounding environment changed. We also found multiple motivations that shaped the use of sports trackers. We identified two main categories in runners’ motivations for using trackers and data to achieve their goals. These categories were (i) documenting and tracking in running, and (ii) supporting goal-oriented reflections and actions, with various reasons for use while preparing for and during running. This study provides insights into the psychological effects of running-related data and signals practical implications for runners and developers of tracking technology. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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Review

Jump to: Research, Other

20 pages, 2191 KiB

Open AccessReview

Wearable and Non-Invasive Sensors for Rock Climbing Applications: Science-Based Training and Performance Optimization

by Miyuki Breen, Taylor Reed, Yoshiko Nishitani, Matthew Jones, Hannah M. Breen and Michael S. Breen

Sensors 2023, 23(11), 5080; https://doi.org/10.3390/s23115080 - 25 May 2023

Cited by 6 | Viewed by 4463

Abstract

Rock climbing has evolved from a method for alpine mountaineering into a popular recreational activity and competitive sport. Advances in safety equipment and the rapid growth of indoor climbing facilities has enabled climbers to focus on the physical and technical movements needed to [...] Read more.

Rock climbing has evolved from a method for alpine mountaineering into a popular recreational activity and competitive sport. Advances in safety equipment and the rapid growth of indoor climbing facilities has enabled climbers to focus on the physical and technical movements needed to elevate performance. Through improved training methods, climbers can now achieve ascents of extreme difficulty. A critical aspect to further improve performance is the ability to continuously measure body movement and physiologic responses while ascending the climbing wall. However, traditional measurement devices (e.g., dynamometer) limit data collection during climbing. Advances in wearable and non-invasive sensor technologies have enabled new applications for climbing. This paper presents an overview and critical analysis of the scientific literature on sensors used during climbing. We focus on the several highlighted sensors with the ability to provide continuous measurements during climbing. These selected sensors consist of five main types (body movement, respiration, heart activity, eye gazing, skeletal muscle characterization) that demonstrate their capabilities and potential climbing applications. This review will facilitate the selection of these types of sensors in support of climbing training and strategies. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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31 pages, 783 KiB

Open AccessReview

Physiological and Biomechanical Monitoring in American Football Players: A Scoping Review

by Antonio Nocera, Agnese Sbrollini, Sofia Romagnoli, Micaela Morettini, Ennio Gambi and Laura Burattini

Sensors 2023, 23(7), 3538; https://doi.org/10.3390/s23073538 - 28 Mar 2023

Cited by 3 | Viewed by 5711

Abstract

American football is the sport with the highest rates of concussion injuries. Biomedical engineering applications may support athletes in monitoring their injuries, evaluating the effectiveness of their equipment, and leading industrial research in this sport. This literature review aims to report on the [...] Read more.

American football is the sport with the highest rates of concussion injuries. Biomedical engineering applications may support athletes in monitoring their injuries, evaluating the effectiveness of their equipment, and leading industrial research in this sport. This literature review aims to report on the applications of biomedical engineering research in American football, highlighting the main trends and gaps. The review followed the PRISMA guidelines and gathered a total of 1629 records from PubMed (n = 368), Web of Science (n = 665), and Scopus (n = 596). The records were analyzed, tabulated, and clustered in topics. In total, 112 studies were selected and divided by topic in the biomechanics of concussion (n = 55), biomechanics of footwear (n = 6), biomechanics of sport-related movements (n = 6), the aerodynamics of football and catch (n = 3), injury prediction (n = 8), heat monitoring of physiological parameters (n = 8), and monitoring of the training load (n = 25). The safety of players has fueled most of the research that has led to innovations in helmet and footwear design, as well as improvements in the understanding and prevention of injuries and heat monitoring. The other important motivator for research is the improvement of performance, which has led to the monitoring of training loads and catches, and studies on the aerodynamics of football. The main gaps found in the literature were regarding the monitoring of internal loads and the innovation of shoulder pads. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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22 pages, 704 KiB

Open AccessReview

Wearable and Portable Devices for Acquisition of Cardiac Signals while Practicing Sport: A Scoping Review

by Sofia Romagnoli, Francesca Ripanti, Micaela Morettini, Laura Burattini and Agnese Sbrollini

Sensors 2023, 23(6), 3350; https://doi.org/10.3390/s23063350 - 22 Mar 2023

Cited by 16 | Viewed by 4324

Abstract

Wearable and portable devices capable of acquiring cardiac signals are at the frontier of the sport industry. They are becoming increasingly popular for monitoring physiological parameters while practicing sport, given the advances in miniaturized technologies, powerful data, and signal processing applications. Data and [...] Read more.

Wearable and portable devices capable of acquiring cardiac signals are at the frontier of the sport industry. They are becoming increasingly popular for monitoring physiological parameters while practicing sport, given the advances in miniaturized technologies, powerful data, and signal processing applications. Data and signals acquired by these devices are increasingly used to monitor athletes’ performances and thus to define risk indices for sport-related cardiac diseases, such as sudden cardiac death. This scoping review investigated commercial wearable and portable devices employed for cardiac signal monitoring during sport activity. A systematic search of the literature was conducted on PubMed, Scopus, and Web of Science. After study selection, a total of 35 studies were included in the review. The studies were categorized based on the application of wearable or portable devices in (1) validation studies, (2) clinical studies, and (3) development studies. The analysis revealed that standardized protocols for validating these technologies are necessary. Indeed, results obtained from the validation studies turned out to be heterogeneous and scarcely comparable, since the metrological characteristics reported were different. Moreover, the validation of several devices was carried out during different sport activities. Finally, results from clinical studies highlighted that wearable devices are crucial to improve athletes’ performance and to prevent adverse cardiovascular events. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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11 pages, 610 KiB

Open AccessReview

Using Artificial Intelligence-Enhanced Sensing and Wearable Technology in Sports Medicine and Performance Optimisation

by Swathikan Chidambaram, Yathukulan Maheswaran, Kian Patel, Viknesh Sounderajah, Daniel A. Hashimoto, Kenneth Patrick Seastedt, Alison H. McGregor, Sheraz R. Markar and Ara Darzi

Sensors 2022, 22(18), 6920; https://doi.org/10.3390/s22186920 - 13 Sep 2022

Cited by 35 | Viewed by 10035

Abstract

Wearable technologies are small electronic and mobile devices with wireless communication capabilities that can be worn on the body as a part of devices, accessories or clothes. Sensors incorporated within wearable devices enable the collection of a broad spectrum of data that can [...] Read more.

Wearable technologies are small electronic and mobile devices with wireless communication capabilities that can be worn on the body as a part of devices, accessories or clothes. Sensors incorporated within wearable devices enable the collection of a broad spectrum of data that can be processed and analysed by artificial intelligence (AI) systems. In this narrative review, we performed a literature search of the MEDLINE, Embase and Scopus databases. We included any original studies that used sensors to collect data for a sporting event and subsequently used an AI-based system to process the data with diagnostic, treatment or monitoring intents. The included studies show the use of AI in various sports including basketball, baseball and motor racing to improve athletic performance. We classified the studies according to the stage of an event, including pre-event training to guide performance and predict the possibility of injuries; during events to optimise performance and inform strategies; and in diagnosing injuries after an event. Based on the included studies, AI techniques to process data from sensors can detect patterns in physiological variables as well as positional and kinematic data to inform how athletes can improve their performance. Although AI has promising applications in sports medicine, there are several challenges that can hinder their adoption. We have also identified avenues for future work that can provide solutions to overcome these challenges. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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21 pages, 875 KiB

Open AccessSystematic Review

Monitoring Internal Load in Women’s Basketball via Subjective and Device-Based Methods: A Systematic Review

by Javier Espasa-Labrador, Azahara Fort-Vanmeerhaeghe, Alicia M. Montalvo, Marta Carrasco-Marginet, Alfredo Irurtia and Julio Calleja-González

Sensors 2023, 23(9), 4447; https://doi.org/10.3390/s23094447 - 2 May 2023

Cited by 9 | Viewed by 2682

Abstract

The monitoring of internal load in basketball can be used to understand the effects and potential physiological adaptations caused by external load. The main aim of this systematic review was to identify the methods and variables used to quantify internal load in female [...] Read more.

The monitoring of internal load in basketball can be used to understand the effects and potential physiological adaptations caused by external load. The main aim of this systematic review was to identify the methods and variables used to quantify internal load in female basketball. The studies included different populations and events: youth athletes, elite, and amateur players. Subjective methods included using the rating of perceived exertion (RPE) method, and sensor-based methods included monitoring the cardiac response to exercise, using heart rate (HR) as the primary metric. The results showed that the HRAvg exhibited a wider range of values during training than during competition, and different metrics were used to evaluate internal load, such as HRMax, HRmin, %HRMax, total time and % of time spent in different HR zones (2–8 zones), Banister’s TRIMP, and summated HR zones. RPE and HR metrics were the most commonly used methods. However, the use of multiple metrics with little standardization resulted in significant heterogeneity among studies, limiting meaningful comparisons. The review provides a reference for current research on female basketball. Future research could address this limitation by adopting more consistent measurement protocols standardizing the use of metrics. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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12 pages, 729 KiB

Open AccessPerspective

Ubiquitous Computing in Sports and Physical Activity—Recent Trends and Developments

by Arnold Baca, Peter Dabnichki, Che-Wei Hu, Philipp Kornfeind and Juliana Exel

Sensors 2022, 22(21), 8370; https://doi.org/10.3390/s22218370 - 1 Nov 2022

Cited by 11 | Viewed by 4404

Abstract

The use of small, interconnected and intelligent tools within the broad framework of pervasive computing for analysis and assessments in sport and physical activity is not a trend in itself but defines a way for information to be handled, processed and utilised: everywhere, [...] Read more.

The use of small, interconnected and intelligent tools within the broad framework of pervasive computing for analysis and assessments in sport and physical activity is not a trend in itself but defines a way for information to be handled, processed and utilised: everywhere, at any time. The demand for objective data to support decision making prompted the adoption of wearables that evolve to fulfil the aims of assessing athletes and practitioners as closely as possible with their performance environments. In the present paper, we mention and discuss the advancements in ubiquitous computing in sports and physical activity in the past 5 years. Thus, recent developments in wearable sensors, cloud computing and artificial intelligence tools have been the pillars for a major change in the ways sport-related analyses are performed. The focus of our analysis is wearable technology, computer vision solutions for markerless tracking and their major contribution to the process of acquiring more representative data from uninhibited actions in realistic ecological conditions. We selected relevant literature on the applications of such approaches in various areas of sports and physical activity while outlining some limitations of the present-day data acquisition and data processing practices and the resulting sensors’ functionalities, as well as the limitations to the data-driven informed decision making in the current technological and scientific framework. Finally, we hypothesise that a continuous merger of measurement, processing and analysis will lead to the development of more reliable models utilising the advantages of open computing and unrestricted data access and allow for the development of personalised-medicine-type approaches to sport training and performance. Full article

(This article belongs to the Special Issue Applications, Wearables and Sensing Technology in Sports and Physical Activity)

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