IMU-based motion capture system for rehabilitation applications: A systematic review

In recent years, the use of inertial measurement unit (IMU)-based motion capture (Mocap) systems in rehabilitation has grown significantly. This paper aimed to provide an overview of current IMU-based Mocap system designs in the field of rehabilitation, explore the specific applications and implemen...

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Main Authors: Chenyu Gu, Weicong Lin, Xinyi He, Lei Zhang, Mingming Zhang
Format: Article
Language:English
Published: Elsevier 2023-06-01
Series:Biomimetic Intelligence and Robotics
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2667379723000116
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author Chenyu Gu
Weicong Lin
Xinyi He
Lei Zhang
Mingming Zhang
author_facet Chenyu Gu
Weicong Lin
Xinyi He
Lei Zhang
Mingming Zhang
author_sort Chenyu Gu
collection DOAJ
description In recent years, the use of inertial measurement unit (IMU)-based motion capture (Mocap) systems in rehabilitation has grown significantly. This paper aimed to provide an overview of current IMU-based Mocap system designs in the field of rehabilitation, explore the specific applications and implementation of these systems, and discuss potential future developments considering sensor limitations. For this review, a systematic literature search was conducted using Scopus, IEEE Xplore, PubMed, and Web of Science from 2013 to 2022. A total of 65 studies were included and analyzed based on their rehabilitation application, target population, and system deployment and measurement. The proportion of rehabilitation assessment, training, and both were 82%, 12%, and 6% respectively. The results showed that primary focus of the studies was stroke that was one of the most commonly studied pathological disease. Additionally, general rehabilitation without targeting a specific pathology was also examined widely, with a particular emphasis on gait analysis. The most common sensor configuration for gait analysis was two IMUs measuring spatiotemporal parameters of the lower limb. However, the lack of training applications and upper limb studies could be attributed to the limited battery life and sensor drift. To address this issue, the use of low-power chips and low-consumption transmission pathways was a potential way to extend usage time for long-term training. Furthermore, we suggest the development of a highly integrated multi-modal system with sensor fusion.
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spelling doaj.art-e198afb6b4ab449f976b206db22960bd2023-06-22T05:05:59ZengElsevierBiomimetic Intelligence and Robotics2667-37972023-06-0132100097IMU-based motion capture system for rehabilitation applications: A systematic reviewChenyu Gu0Weicong Lin1Xinyi He2Lei Zhang3Mingming Zhang4Shenzhen Key Laboratory of Smart Healthcare Engineering, Department of Biomedical Engineering, Southern University of Science and Technology, Shenzhen 518055, ChinaShenzhen Key Laboratory of Smart Healthcare Engineering, Department of Biomedical Engineering, Southern University of Science and Technology, Shenzhen 518055, ChinaShenzhen Key Laboratory of Smart Healthcare Engineering, Department of Biomedical Engineering, Southern University of Science and Technology, Shenzhen 518055, ChinaShenzhen Key Laboratory of Smart Healthcare Engineering, Department of Biomedical Engineering, Southern University of Science and Technology, Shenzhen 518055, ChinaCorresponding author.; Shenzhen Key Laboratory of Smart Healthcare Engineering, Department of Biomedical Engineering, Southern University of Science and Technology, Shenzhen 518055, ChinaIn recent years, the use of inertial measurement unit (IMU)-based motion capture (Mocap) systems in rehabilitation has grown significantly. This paper aimed to provide an overview of current IMU-based Mocap system designs in the field of rehabilitation, explore the specific applications and implementation of these systems, and discuss potential future developments considering sensor limitations. For this review, a systematic literature search was conducted using Scopus, IEEE Xplore, PubMed, and Web of Science from 2013 to 2022. A total of 65 studies were included and analyzed based on their rehabilitation application, target population, and system deployment and measurement. The proportion of rehabilitation assessment, training, and both were 82%, 12%, and 6% respectively. The results showed that primary focus of the studies was stroke that was one of the most commonly studied pathological disease. Additionally, general rehabilitation without targeting a specific pathology was also examined widely, with a particular emphasis on gait analysis. The most common sensor configuration for gait analysis was two IMUs measuring spatiotemporal parameters of the lower limb. However, the lack of training applications and upper limb studies could be attributed to the limited battery life and sensor drift. To address this issue, the use of low-power chips and low-consumption transmission pathways was a potential way to extend usage time for long-term training. Furthermore, we suggest the development of a highly integrated multi-modal system with sensor fusion.http://www.sciencedirect.com/science/article/pii/S2667379723000116Motion capture systemRehabilitationInertial measurement unitSystematic review
spellingShingle Chenyu Gu
Weicong Lin
Xinyi He
Lei Zhang
Mingming Zhang
IMU-based motion capture system for rehabilitation applications: A systematic review
Biomimetic Intelligence and Robotics
Motion capture system
Rehabilitation
Inertial measurement unit
Systematic review
title IMU-based motion capture system for rehabilitation applications: A systematic review
title_full IMU-based motion capture system for rehabilitation applications: A systematic review
title_fullStr IMU-based motion capture system for rehabilitation applications: A systematic review
title_full_unstemmed IMU-based motion capture system for rehabilitation applications: A systematic review
title_short IMU-based motion capture system for rehabilitation applications: A systematic review
title_sort imu based motion capture system for rehabilitation applications a systematic review
topic Motion capture system
Rehabilitation
Inertial measurement unit
Systematic review
url http://www.sciencedirect.com/science/article/pii/S2667379723000116
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