A review of computer vision-based approaches for physical rehabilitation and assessment

BAPPADITYA DEBNATH, MARY O'BRIEN, MOTONORI YAMAGUCHI, ARDHENDU BEHERA

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Abstract

The 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.
Original languageEnglish
JournalMultimedia Systems
DOIs
Publication statusPublished - 19 Jun 2021

Keywords

  • Computer Vision
  • Stroke
  • Physical rehabilitation
  • Patient monitoring
  • Patient Assessment
  • Artificial intelligence

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