惯性测量装置
康复
计算机科学
运动捕捉
软件部署
物理医学与康复
人口
人工智能
运动(物理)
医学
物理疗法
环境卫生
操作系统
作者
Chenyu Gu,Weicong Lin,Xinyi He,Lei Zhang,Mingming Zhang
标识
DOI:10.1016/j.birob.2023.100097
摘要
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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