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The Role of Multi-Sensor Measurement in the Assessment of Movement Quality: A Systematic Review

BACKGROUND: Movement quality is typically assessed by drawing comparisons against predetermined movement standards. Movements are often discretely scored or labelled against pre-set criteria, though movement quality can also be evaluated using motion-related measurements (e.g., spatio-temporal param...

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Autores principales: Swain, T. Alexander, McNarry, Melitta A., Runacres, Adam W. H., Mackintosh, Kelly A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10687099/
https://www.ncbi.nlm.nih.gov/pubmed/37698766
http://dx.doi.org/10.1007/s40279-023-01905-1
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author Swain, T. Alexander
McNarry, Melitta A.
Runacres, Adam W. H.
Mackintosh, Kelly A.
author_facet Swain, T. Alexander
McNarry, Melitta A.
Runacres, Adam W. H.
Mackintosh, Kelly A.
author_sort Swain, T. Alexander
collection PubMed
description BACKGROUND: Movement quality is typically assessed by drawing comparisons against predetermined movement standards. Movements are often discretely scored or labelled against pre-set criteria, though movement quality can also be evaluated using motion-related measurements (e.g., spatio-temporal parameters and kinematic variables). Wearable technology has the potential to measure and assess movement quality and offer valuable, practical feedback. OBJECTIVES: A systematic approach was taken to examine the benefits associated with multi-sensor and multiple wearable-device usage, compared with unimodal applications, when assessing movement quality. Consequently, this review considers the additional variables and features that could be obtained through multi-sensor devices for use in movement analyses. Processing methods and applications of the various configurations were also explored. METHODS: Articles were included within this review if they were written in English, specifically studied the use of wearable sensors to assess movement quality, and were published between January 2010 and December 2022. Of the 62,635 articles initially identified, 27 papers were included in this review. The quality of included studies was determined using a modified Downs and Black checklist, with 24/27 high quality. RESULTS: Fifteen of the 27 included studies used a classification approach, 11 used a measurement approach, and one used both methods. Accelerometers featured in all 27 studies, in isolation (n = 5), with a gyroscope (n = 9), or with both a gyroscope and a magnetometer (n = 13). Sampling frequencies across all studies ranged from 50 to 200 Hz. The most common classification methods were traditional feature-based classifiers (n = 5) and support vector machines (SVM; n = 5). Sensor fusion featured in six of the 16 classification studies and nine of the 12 measurement studies, with the Madgwick algorithm most prevalent (n = 7). CONCLUSIONS: This systematic review highlights the differences between the applications and processing methods associated with the use of unimodal and multi-sensor wearable devices when assessing movement quality. Further, the use of multiple devices appears to increase the feasibility of effectively assessing holistic movements, while multi-sensor devices offer the ability to obtain more output metrics. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40279-023-01905-1.
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spelling pubmed-106870992023-12-01 The Role of Multi-Sensor Measurement in the Assessment of Movement Quality: A Systematic Review Swain, T. Alexander McNarry, Melitta A. Runacres, Adam W. H. Mackintosh, Kelly A. Sports Med Systematic Review BACKGROUND: Movement quality is typically assessed by drawing comparisons against predetermined movement standards. Movements are often discretely scored or labelled against pre-set criteria, though movement quality can also be evaluated using motion-related measurements (e.g., spatio-temporal parameters and kinematic variables). Wearable technology has the potential to measure and assess movement quality and offer valuable, practical feedback. OBJECTIVES: A systematic approach was taken to examine the benefits associated with multi-sensor and multiple wearable-device usage, compared with unimodal applications, when assessing movement quality. Consequently, this review considers the additional variables and features that could be obtained through multi-sensor devices for use in movement analyses. Processing methods and applications of the various configurations were also explored. METHODS: Articles were included within this review if they were written in English, specifically studied the use of wearable sensors to assess movement quality, and were published between January 2010 and December 2022. Of the 62,635 articles initially identified, 27 papers were included in this review. The quality of included studies was determined using a modified Downs and Black checklist, with 24/27 high quality. RESULTS: Fifteen of the 27 included studies used a classification approach, 11 used a measurement approach, and one used both methods. Accelerometers featured in all 27 studies, in isolation (n = 5), with a gyroscope (n = 9), or with both a gyroscope and a magnetometer (n = 13). Sampling frequencies across all studies ranged from 50 to 200 Hz. The most common classification methods were traditional feature-based classifiers (n = 5) and support vector machines (SVM; n = 5). Sensor fusion featured in six of the 16 classification studies and nine of the 12 measurement studies, with the Madgwick algorithm most prevalent (n = 7). CONCLUSIONS: This systematic review highlights the differences between the applications and processing methods associated with the use of unimodal and multi-sensor wearable devices when assessing movement quality. Further, the use of multiple devices appears to increase the feasibility of effectively assessing holistic movements, while multi-sensor devices offer the ability to obtain more output metrics. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40279-023-01905-1. Springer International Publishing 2023-09-12 2023 /pmc/articles/PMC10687099/ /pubmed/37698766 http://dx.doi.org/10.1007/s40279-023-01905-1 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Systematic Review
Swain, T. Alexander
McNarry, Melitta A.
Runacres, Adam W. H.
Mackintosh, Kelly A.
The Role of Multi-Sensor Measurement in the Assessment of Movement Quality: A Systematic Review
title The Role of Multi-Sensor Measurement in the Assessment of Movement Quality: A Systematic Review
title_full The Role of Multi-Sensor Measurement in the Assessment of Movement Quality: A Systematic Review
title_fullStr The Role of Multi-Sensor Measurement in the Assessment of Movement Quality: A Systematic Review
title_full_unstemmed The Role of Multi-Sensor Measurement in the Assessment of Movement Quality: A Systematic Review
title_short The Role of Multi-Sensor Measurement in the Assessment of Movement Quality: A Systematic Review
title_sort role of multi-sensor measurement in the assessment of movement quality: a systematic review
topic Systematic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10687099/
https://www.ncbi.nlm.nih.gov/pubmed/37698766
http://dx.doi.org/10.1007/s40279-023-01905-1
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