A review of computer vision-based approaches for physical rehabilitation and assessment
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Published:2021-06-19
Issue:1
Volume:28
Page:209-239
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ISSN:0942-4962
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Container-title:Multimedia Systems
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language:en
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Short-container-title:Multimedia Systems
Author:
Debnath BappadityaORCID, O’Brien Mary, Yamaguchi Motonori, Behera Ardhendu
Abstract
AbstractThe computer vision community has extensively researched the area of human motion analysis, which primarily focuses on pose estimation, activity recognition, pose or gesture recognition and so on. However for many applications, like monitoring of functional rehabilitation of patients with musculo skeletal or physical impairments, the requirement is to comparatively evaluate human motion. In this survey, we capture important literature on vision-based monitoring and physical rehabilitation that focuses on comparative evaluation of human motion during the past two decades and discuss the state of current research in this area. Unlike other reviews in this area, which are written from a clinical objective, this article presents research in this area from a computer vision application perspective. We propose our own taxonomy of computer vision-based rehabilitation and assessment research which are further divided into sub-categories to capture novelties of each research. The review discusses the challenges of this domain due to the wide ranging human motion abnormalities and difficulty in automatically assessing those abnormalities. Finally, suggestions on the future direction of research are offered.
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Information Systems,Software
Reference164 articles.
1. Adams, R.J., Lichter, M.D., Krepkovich, E.T., Ellington, A., White, M., Diamond, P.T.: Assessing upper extremity motor function in practice of virtual activities of daily living. IEEE Trans. Neural Syst. Rehabil. Eng. 23(2), 287–296 (2015) 2. Ahad, Md Atiqur Rahman, Antar, Anindya Das, Shahid, Omar: Vision-based action understanding for assistive healthcare: A short review. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops 2019, pp. 1–11 (2019) 3. Antón, D., Goñi, A., Illarramendi, A., Torres-Unda, J.J.: Jesús Seco. Kires: A kinect-based telerehabilitation system. In: e-Health Networking, Applications & Services (Healthcom), 2013 IEEE 15th International Conference on, pp. 444–448. IEEE (2013) 4. Antoniou, A., Storkey, A., Edwards, H.: Data augmentation generative adversarial networks. arXiv:1711.04340 (2017) 5. Antunes, J., Bernardino, A., Smailagic, A., Siewiorek, D.P.: Aha-3d: A labelled dataset for senior fitness exercise recognition and segmentation from 3d skeletal data. In: BMVC, pp. 332 (2018)
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