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Wearable Sensors for Optimising Rehabilitation and Sport Training
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Wearable Sensors for Optimising Rehabilitation and Sport Training

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Wearables".

Deadline for manuscript submissions: 20 December 2025 | Viewed by 4956

Special Issue Editor

Dr. Mohsen Shafizadeh

E-Mail Website
Guest Editor
Academy of Sport and Physical Activity, Sheffield Hallam University, Sheffield S10 2BP, UK
Interests: rehabilitation technologies; biomechanics; motor control

Special Issue Information

Dear Colleagues,

The applications of wearable technologies/sensors in rehabilitation and sport performance are growing, and many practitioners use feedback tools to communicate with end-users for the assessment, diagnosis, and monitoring of body conditions. The area of intervention design using such technologies is still not well studied and requires more evidence to prove the effectiveness of wearable sensors in optimising rehabilitation outcomes and sports training. The aim of this Special Issue is to advance our understanding of the applications of any kind of wearable technologies in the rehabilitation of functional movements (such as gait and running), muscle activities, sport performance, recovery after sports injuries, and general health. We accept quantitative studies in the form of original research, review studies, and meta-analyses that have not been submitted or published in other journals.

Dr. Mohsen Shafizadeh
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • inertial motion units (IMU)
  • wireless electromyography (EMG)
  • global positioning system (GPS)
  • sport injuries
  • sport rehabilitation
  • physical therapy
  • gait retraining
  • technology
  • training
  • wearable sensors

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Published Papers (6 papers)

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Research

15 pages, 3737 KiB  
Article
Validation and Analysis of Recreational Runners’ Kinematics Obtained from a Sacral IMU
by Hossein Asgari and Ben Heller
Sensors 2025, 25(2), 315; https://doi.org/10.3390/s25020315 - 7 Jan 2025
Viewed by 672
Abstract
Our aim was to validate a sacral-mounted inertial measurement unit (IMU) for reconstructing running kinematics and comparing movement patterns within and between runners. IMU data were processed using Kalman and complementary filters separately. RMSE and Bland–Altman analysis assessed the validity of each filtering [...] Read more.
Our aim was to validate a sacral-mounted inertial measurement unit (IMU) for reconstructing running kinematics and comparing movement patterns within and between runners. IMU data were processed using Kalman and complementary filters separately. RMSE and Bland–Altman analysis assessed the validity of each filtering method against a motion capture system. Running data from 24 recreational runners were analyzed using Fourier transform coefficients, PCA, and k-means clustering. High agreement was found for Kalman-filtered data in the frontal, sagittal, and transverse planes, with a Bland–Altman bias of ~2 mm on average, compared to a bias of ~10.5 mm for complementary-filtered data. Pelvic angles calculated from Kalman-filtered data had superior agreement, with systematic biases of ~0.3 versus 3.4 degrees for complementary-filtered data. Our findings suggest that inertial sensors are viable alternatives to motion capture for reconstructing pelvic running kinematics and movement patterns. In the second part of our study, negligible intra-individual differences were observed with changes in speed, while inter-individual differences were large. Two clusters of runners were identified, each showing distinct movement patterns and ranges of motion. These observations highlight the potential usefulness of inertial sensors for performance analysis and rehabilitation as they may permit the use of individual-specific and cluster-specific practice programs. Full article
(This article belongs to the Special Issue Wearable Sensors for Optimising Rehabilitation and Sport Training)
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12 pages, 416 KiB  
Article
The Use of Principal Component Analysis for Reduction in Sleep Quality and Quantity Data in Female Professional Soccer
by Eider Barba, David Casamichana, Pedro Figueiredo, Fábio Yuzo Nakamura and Julen Castellano
Sensors 2025, 25(1), 148; https://doi.org/10.3390/s25010148 - 30 Dec 2024
Viewed by 571
Abstract
The main aim of the present study was to uncover multivariate relationships between sleep quantity and quality using principal component analysis (PCA) in professional female soccer players. A second aim was to examine the extent to which objective sleep quantity and quality variables [...] Read more.
The main aim of the present study was to uncover multivariate relationships between sleep quantity and quality using principal component analysis (PCA) in professional female soccer players. A second aim was to examine the extent to which objective sleep quantity and quality variables can discriminate between perceived sleep. Ten objective sleep variables from the multisensory sleep-tracker were analyzed. PCA was conducted on the sleep variables, and meaningful principal components (PCs) were identified (eigenvalue > 2). Two sleep PCs were identified, representing the ‘quantity of sleep’ (quantity PC: eigenvalue = 4.1 and variance explained = 45.1%) and the ‘quality of sleep’ (quality PC: eigenvalue = 2.4 and variance explained = 24.1%). Cluster analysis grouped the players’ sleep into three types: long and efficient, short and efficient, and long and inefficient; however, no association was found between the perceived sleep and the sleep clusters. In conclusion, a combination of both quantity and quality sleep metrics is recommended for sleep monitoring of professional female soccer players. Players should undergo a training process to improve self-assessment of sleep quality recorded from a subjective questionnaire, contrasting the perceived information with the sleep quality recorded objectively during a defined period in order to optimize the validity of their perceptions. The aim is to optimize the validity of their perceptions of sleep quality. Full article
(This article belongs to the Special Issue Wearable Sensors for Optimising Rehabilitation and Sport Training)
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16 pages, 3327 KiB  
Article
Wearable System Applications in Performance Analysis of RaceRunning Athletes with Disabilities
by Mohsen Shafizadeh and Keith Davids
Sensors 2024, 24(24), 7923; https://doi.org/10.3390/s24247923 - 11 Dec 2024
Viewed by 627
Abstract
RaceRunning is a sport for disabled people and successful performance depends on reducing the amount of time spent travelling a specific distance. Performance analysis in RaceRunning athletes is based on traditional methods such as recording race time, distances travelled and frequency (sets and [...] Read more.
RaceRunning is a sport for disabled people and successful performance depends on reducing the amount of time spent travelling a specific distance. Performance analysis in RaceRunning athletes is based on traditional methods such as recording race time, distances travelled and frequency (sets and reps) that are not sufficient for monitoring training loads. The aims of this study were to monitor training loads in typical training sessions and evaluate technical adaptations in RaceRunning performance by acquiring sensor metrics. Five elite and competitive RaceRunning athletes (18.2 ± 2.3 yrs) at RR2 and RR3 levels were monitored for 8 weeks, performing in their usual training sessions while wearing unobtrusive motion sensors. The motion sensors were attached to the waist and lower leg in all training sessions, each lasting between 80 and 90 min. Performance metrics data collected from the motion sensors included player loads, race loads, work/rest ratio and impact shock directions, along with training factors (duration, frequency, distance, race time and rest time). Results showed that weekly training loads (player and race loads) followed acceptable threshold levels, according to assessment criteria (smallest worthwhile change, acute/chronic work ratio). The relationship between race velocity (performance index) and race load was non-linear and statistically significant, which led to different performance efficiency groups. Wearable motion sensor metrics revealed small to moderate technical adaptations following repeated sprint attempts in temporal running performance, variability and consistency. In conclusion, using a wearable-based system is an effective feedback tool to monitor training quality, revealing important insights into adaptations to training volumes in disabled athletes. Full article
(This article belongs to the Special Issue Wearable Sensors for Optimising Rehabilitation and Sport Training)
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9 pages, 2256 KiB  
Communication
Progressive and Asymmetrical Deadlift Loads Captured by Wearable Motion Tape Sensors
by Elijah Wyckoff, David Sten, Regan Wareham and Kenneth J. Loh
Sensors 2024, 24(23), 7700; https://doi.org/10.3390/s24237700 - 2 Dec 2024
Viewed by 806
Abstract
Weight training is widely adopted and highly effective for enhancing both muscular strength and endurance. A popular weightlifting exercise is the deadlift, which targets multiple muscle groups including the lower back, glutes, and hamstrings. However, incorrect technique (i.e., poor form) can slow training [...] Read more.
Weight training is widely adopted and highly effective for enhancing both muscular strength and endurance. A popular weightlifting exercise is the deadlift, which targets multiple muscle groups including the lower back, glutes, and hamstrings. However, incorrect technique (i.e., poor form) can slow training progress, result in asymmetrical muscle development, and cause serious injuries. The objective of this study was to validate that a self-adhesive, elastic fabric, wearable, skin-strain sensor called Motion Tape (MT) could monitor a person’s posture while performing deadlift exercises. Two pairs of Motion Tape were attached on the front and back sides of the pelvis at each posterior superior iliac spine to record muscle engagement during deadlift exercises. The results of this preliminary study confirmed that the MT identified asymmetry in muscle engagement during deadlifting repetitions. In addition, the sensors could quantify the different levels of effort exerted according to the deadlift weight load. Full article
(This article belongs to the Special Issue Wearable Sensors for Optimising Rehabilitation and Sport Training)
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9 pages, 709 KiB  
Article
Running Gait Complexity During an Overground, Mass-Participation Five-Kilometre Run
by Ben Jones, Ben Heller, Linda van Gelder, Andrew Barnes, Joanna Reeves and Jon Wheat
Sensors 2024, 24(22), 7252; https://doi.org/10.3390/s24227252 - 13 Nov 2024
Viewed by 905
Abstract
Human locomotion contains innate variability which may provide health insights. Detrended fluctuation analysis (DFA) has been used to quantify the temporal structure of variability for treadmill running, although it has been less commonly applied to uncontrolled overground running. This study aimed to determine [...] Read more.
Human locomotion contains innate variability which may provide health insights. Detrended fluctuation analysis (DFA) has been used to quantify the temporal structure of variability for treadmill running, although it has been less commonly applied to uncontrolled overground running. This study aimed to determine how running gait complexity changes in response to gradient and elapsed exercise duration during uncontrolled overground running. Sixty-eight participants completed an overground, mass-participation five-kilometre run (a parkrun). Stride times were recorded using an inertial measurement unit mounted on the distal shank. Data were divided into four consecutive intervals (uphill lap 1, downhill lap 1, uphill lap 2, downhill lap 2). The magnitude (SD) and structure (DFA) of stride time variability were compared across elapsed exercise duration and gradient using a repeated-measures ANOVA. Participants maintained consistent stride times throughout the run. Stride time DFA-α displayed a moderate decrease (d = |0.39| ± 0.13) during downhill running compared to uphill running. DFA-α did not change in response to elapsed exercise duration, although a greater stride time SD was found during the first section of lap 1 (d = |0.30| ± 0.12). These findings suggest that inter- and intra-run changes in gait complexity should be interpreted in the context of course elevation profiles before conclusions on human health are drawn. Full article
(This article belongs to the Special Issue Wearable Sensors for Optimising Rehabilitation and Sport Training)
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15 pages, 3530 KiB  
Article
Predicting Athlete Workload in Women’s Rugby Sevens Using GNSS Sensor Data, Contact Count and Mass
by Amarah Epp-Stobbe, Ming-Chang Tsai and Marc D. Klimstra
Sensors 2024, 24(20), 6699; https://doi.org/10.3390/s24206699 - 18 Oct 2024
Viewed by 760
Abstract
The use of session rating of perceived exertion (sRPE) as a measure of workload is a popular athlete load monitoring tool. However, the nature of sRPE means the contribution of salient, sport-specific factors to athlete load in field sports is challenging to isolate [...] Read more.
The use of session rating of perceived exertion (sRPE) as a measure of workload is a popular athlete load monitoring tool. However, the nature of sRPE means the contribution of salient, sport-specific factors to athlete load in field sports is challenging to isolate and quantify. In rugby sevens, drivers of load include high-speed running and physical contact. In soccer and men’s rugby, union acceleration/deceleration also influences load. These metrics are evaluated using data from global navigation satellite system (GNSS) sensors worn by athletes. Research suggests that sensor data methods for identifying load in men’s rugby do not accurately quantify female athlete loads. This investigation examined how mass, contact, and accelerations and decelerations at different speeds contribute to load in women’s rugby sevens. The study evaluated 99 international matches, using data from 19 full-time athletes. GNSS measures, RPE, athlete mass, and contact count were evaluated using a linear mixed-model regression. The model demonstrated significant effects for low decelerations at low and high speeds, mass, distance, and contact count explaining 48.7% of the global variance of sRPE. The use of acceleration/deceleration and speed from GNSS sensors alongside mass, as well as contact count, presents a novel approach to quantifying load. Full article
(This article belongs to the Special Issue Wearable Sensors for Optimising Rehabilitation and Sport Training)
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