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Novel Applications of Sensors Technology for Motion Analysis to Advance Understanding of Human Movement

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

Deadline for manuscript submissions: closed (25 March 2024) | Viewed by 8881

Special Issue Editors

Dr. Matthew A. Timmis

E-Mail Website
Guest Editor
Cambridge Centre for Sport and Exercise Sciences (CCSES), School of Psychology and Sport Science, Anglia Ruskin University, Cambridge CB1 1PT, UK
Interests: vision impairment and human movement; visual search and its impact on human movement
Dr. Andrew Morrison

E-Mail Website
Guest Editor
Cambridge Centre for Sport and Exercise Sciences (CCSES), School of Psychology and Sport Science, Anglia Ruskin University, Cambridge CB1 1PT, UK
Interests: non-linear analysis of human movement; wearable technology for gait analysis
Dr. Dan Robbins

E-Mail Website
Guest Editor
Biomechanics, Optics, Robotics and Imaging Research Group, Medical Technology Research Centre, Anglia Ruskin University, Chelmsford CM1 1SQ, UK
Interests: structure and function of the human body, focusing on peripheral neurophysiology and vascular function
Dr. Matthew J. D. Taylor

E-Mail Website
Guest Editor
School of Sport Rehabilitation and Exercise Science, University of Essex, Essex, UK
Interests: gait analysis; falls; human movement

Special Issue Information

Dear Colleagues,

Drs Timmis, Morrison, Robbins and Taylor are pleased to serve as Guest Editors for an upcoming Special Issue titled “Novel Applications of Sensors Technology for Motion Analysis to Advance Understanding of Human Movement”.

Technological advancements have created exciting opportunities for the analysis of human movement in novel and applied environments, enabling research to be conducted in more ecologically representative environments (i.e., beyond laboratory testing).

This Special Issue will provide an opportunity to disseminate innovative approaches currently being undertaken to either enhance performance, minimize injury risk or monitor/diagnose pathology. We welcome submissions across the broad spectrum of Sport and Clinical Biomechanics, investigating either paediatric or adult populations. It is anticipated that the following technology is highlighted:

  • Alternative applications of motion capture;
  • Use of wearable technology (e.g., IMUs);
  • Embedded technology (e.g., sensory in clothing);
  • Markerless motion capture systems;
  • Virtual reality.

Dr. Matthew A. Timmis
Dr. Andrew Morrison
Dr. Dan Robbins
Dr. Matthew J. D. Taylor
Guest Editors

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

  • biomechanics
  • human movement
  • gait pathology
  • injury
  • performance
  • gait

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Published Papers (5 papers)

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Research

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14 pages, 1576 KiB  
Article
Dynamic Stability, Symmetry, and Smoothness of Gait in People with Neurological Health Conditions
by Marco Tramontano, Amaranta Soledad Orejel Bustos, Rebecca Montemurro, Simona Vasta, Gabriele Marangon, Valeria Belluscio, Giovanni Morone, Nicola Modugno, Maria Gabriella Buzzi, Rita Formisano, Elena Bergamini and Giuseppe Vannozzi
Sensors 2024, 24(8), 2451; https://doi.org/10.3390/s24082451 - 11 Apr 2024
Cited by 2 | Viewed by 1389
Abstract
Neurological disorders such as stroke, Parkinson’s disease (PD), and severe traumatic brain injury (sTBI) are leading global causes of disability and mortality. This study aimed to assess the ability to walk of patients with sTBI, stroke, and PD, identifying the differences in dynamic [...] Read more.
Neurological disorders such as stroke, Parkinson’s disease (PD), and severe traumatic brain injury (sTBI) are leading global causes of disability and mortality. This study aimed to assess the ability to walk of patients with sTBI, stroke, and PD, identifying the differences in dynamic postural stability, symmetry, and smoothness during various dynamic motor tasks. Sixty people with neurological disorders and 20 healthy participants were recruited. Inertial measurement unit (IMU) sensors were employed to measure spatiotemporal parameters and gait quality indices during different motor tasks. The Mini-BESTest, Berg Balance Scale, and Dynamic Gait Index Scoring were also used to evaluate balance and gait. People with stroke exhibited the most compromised biomechanical patterns, with lower walking speed, increased stride duration, and decreased stride frequency. They also showed higher upper body instability and greater variability in gait stability indices, as well as less gait symmetry and smoothness. PD and sTBI patients displayed significantly different temporal parameters and differences in stability parameters only at the pelvis level and in the smoothness index during both linear and curved paths. This study provides a biomechanical characterization of dynamic stability, symmetry, and smoothness in people with stroke, sTBI, and PD using an IMU-based ecological assessment. Full article
(This article belongs to the Special Issue Novel Applications of Sensors Technology for Motion Analysis to Advance Understanding of Human Movement)
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17 pages, 5130 KiB  
Article
Dual-Task Interference Effects on Lower-Extremity Muscle Activities during Gait Initiation and Steady-State Gait among Healthy Young Individuals, Measured Using Wireless Electromyography Sensors
by Ke’Vaughn Tarrel Waldon, Angeloh Stout, Kaitlin Manning, Leslie Gray, David George Wilson and Gu Eon Kang
Sensors 2023, 23(21), 8842; https://doi.org/10.3390/s23218842 - 31 Oct 2023
Cited by 1 | Viewed by 1524
Abstract
To maintain a healthy lifestyle, adults rely on their ability to walk while simultaneously managing multiple tasks that challenge their coordination. This study investigates the impact of cognitive dual tasks on lower-limb muscle activities in 21 healthy young adults during both gait initiation [...] Read more.
To maintain a healthy lifestyle, adults rely on their ability to walk while simultaneously managing multiple tasks that challenge their coordination. This study investigates the impact of cognitive dual tasks on lower-limb muscle activities in 21 healthy young adults during both gait initiation and steady-state gait. We utilized wireless electromyography sensors to measure muscle activities, along with a 3D motion capture system and force plates to detect the phases of gait initiation and steady-state gait. The participants were asked to walk at their self-selected pace, and we compared single-task and dual-task conditions. We analyzed mean muscle activation and coactivation in the biceps femoris, vastus lateralis, gastrocnemius, and tibialis anterior muscles. The findings revealed that, during gait initiation with the dual-task condition, there was a decrease in mean muscle activation and an increase in mean muscle coactivation between the swing and stance limbs compared with the single-task condition. In steady-state gait, there was also a decrease in mean muscle activation in the dual-task condition compared with the single-task condition. When participants performed dual-task activities during gait initiation, early indicators of reduced balance capability were observed. Additionally, during dual-task steady-state gait, the knee stabilizer muscles exhibited signs of altered activation, contributing to balance instability. Full article
(This article belongs to the Special Issue Novel Applications of Sensors Technology for Motion Analysis to Advance Understanding of Human Movement)
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16 pages, 6441 KiB  
Article
Approaches for Hybrid Coregistration of Marker-Based and Markerless Coordinates Describing Complex Body/Object Interactions
by Hyeonseok Kim, Makoto Miyakoshi and John Rehner Iversen
Sensors 2023, 23(14), 6542; https://doi.org/10.3390/s23146542 - 20 Jul 2023
Cited by 2 | Viewed by 1160
Abstract
Full-body motion capture is essential for the study of body movement. Video-based, markerless, mocap systems are, in some cases, replacing marker-based systems, but hybrid systems are less explored. We develop methods for coregistration between 2D video and 3D marker positions when precise spatial [...] Read more.
Full-body motion capture is essential for the study of body movement. Video-based, markerless, mocap systems are, in some cases, replacing marker-based systems, but hybrid systems are less explored. We develop methods for coregistration between 2D video and 3D marker positions when precise spatial relationships are not known a priori. We illustrate these methods on three-ball cascade juggling in which it was not possible to use marker-based tracking of the balls, and no tracking of the hands was possible due to occlusion. Using recorded video and motion capture, we aimed to transform 2D ball coordinates into 3D body space as well as recover details of hand motion. We proposed four linear coregistration methods that differ in how they optimize ball-motion constraints during hold and flight phases, using an initial estimate of hand position based on arm and wrist markers. We found that minimizing the error between ball and hand estimate was globally suboptimal, distorting ball flight trajectories. The best-performing method used gravitational constraints to transform vertical coordinates and ball-hold constraints to transform lateral coordinates. This method enabled an accurate description of ball flight as well as a reconstruction of wrist movements. We discuss these findings in the broader context of video/motion capture coregistration. Full article
(This article belongs to the Special Issue Novel Applications of Sensors Technology for Motion Analysis to Advance Understanding of Human Movement)
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14 pages, 1785 KiB  
Article
Temporal, Kinematic and Kinetic Variables Derived from a Wearable 3D Inertial Sensor to Estimate Muscle Power during the 5 Sit to Stand Test in Older Individuals: A Validation Study
by Gianluca Bochicchio, Luca Ferrari, Alberto Bottari, Francesco Lucertini, Alessandra Scarton and Silvia Pogliaghi
Sensors 2023, 23(10), 4802; https://doi.org/10.3390/s23104802 - 16 May 2023
Cited by 4 | Viewed by 1713
Abstract
The 5-Sit-to-stand test (5STS) is widely used to estimate lower limb muscle power (MP). An Inertial Measurement Unit (IMU) could be used to obtain objective, accurate and automatic measures of lower limb MP. In 62 older adults (30 F, 66 ± 6 years) [...] Read more.
The 5-Sit-to-stand test (5STS) is widely used to estimate lower limb muscle power (MP). An Inertial Measurement Unit (IMU) could be used to obtain objective, accurate and automatic measures of lower limb MP. In 62 older adults (30 F, 66 ± 6 years) we compared (paired t-test, Pearson’s correlation coefficient, and Bland-Altman analysis) IMU-based estimates of total trial time (totT), mean concentric time (McT), velocity (McV), force (McF), and MP against laboratory equipment (Lab). While significantly different, Lab vs. IMU measures of totT (8.97 ± 2.44 vs. 8.86 ± 2.45 s, p = 0.003), McV (0.35 ± 0.09 vs. 0.27 ± 0.10 m∙s−1, p < 0.001), McF (673.13 ± 146.43 vs. 653.41 ± 144.58 N, p < 0.001) and MP (233.00 ± 70.83 vs. 174.84 ± 71.16 W, p < 0.001) had a very large to extremely large correlation (r = 0.99, r = 0.93, and r = 0.97 r = 0.76 and r = 0.79, respectively, for totT, McT, McF, McV and MP). Bland–Altman analysis showed a small, significant bias and good precision for all the variables, but McT. A sensor-based 5STS evaluation appears to be a promising objective and digitalized measure of MP. This approach could offer a practical alternative to the gold standard methods used to measure MP. Full article
(This article belongs to the Special Issue Novel Applications of Sensors Technology for Motion Analysis to Advance Understanding of Human Movement)
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Review

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19 pages, 946 KiB  
Review
A Scoping Review of the Validity and Reliability of Smartphone Accelerometers When Collecting Kinematic Gait Data
by Clare Strongman, Francesca Cavallerio, Matthew A. Timmis and Andrew Morrison
Sensors 2023, 23(20), 8615; https://doi.org/10.3390/s23208615 - 20 Oct 2023
Viewed by 2068
Abstract
The aim of this scoping review is to evaluate and summarize the existing literature that considers the validity and/or reliability of smartphone accelerometer applications when compared to ‘gold standard’ kinematic data collection (for example, motion capture). An electronic keyword search was performed on [...] Read more.
The aim of this scoping review is to evaluate and summarize the existing literature that considers the validity and/or reliability of smartphone accelerometer applications when compared to ‘gold standard’ kinematic data collection (for example, motion capture). An electronic keyword search was performed on three databases to identify appropriate research. This research was then examined for details of measures and methodology and general study characteristics to identify related themes. No restrictions were placed on the date of publication, type of smartphone, or participant demographics. In total, 21 papers were reviewed to synthesize themes and approaches used and to identify future research priorities. The validity and reliability of smartphone-based accelerometry data have been assessed against motion capture, pressure walkways, and IMUs as ‘gold standard’ technology and they have been found to be accurate and reliable. This suggests that smartphone accelerometers can provide a cheap and accurate alternative to gather kinematic data, which can be used in ecologically valid environments to potentially increase diversity in research participation. However, some studies suggest that body placement may affect the accuracy of the result, and that position data correlate better than actual acceleration values, which should be considered in any future implementation of smartphone technology. Future research comparing different capture frequencies and resulting noise, and different walking surfaces, would be useful. Full article
(This article belongs to the Special Issue Novel Applications of Sensors Technology for Motion Analysis to Advance Understanding of Human Movement)
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