A Dynamic Time Warping Based Algorithm to Evaluate Kinect-Enabled Home-Based Physical Rehabilitation Exercises for Older People

• Published in: Sensors (Basel, Switzerland) Vol. 19; no. 13; p. 2882
• Main Authors: Yu, Xiaoqun, Xiong, Shuping
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 28.06.2019; MDPI
• Subjects: Aged; Aged, 80 and over; aging; Algorithms; automatic coaching; dynamic time warping; Exercise; Exercise - physiology; Exercise Therapy - methods; exergame; Female; Humans; International conferences; Kinect; Male; Motion capture; Older people; Performance evaluation; Physical fitness; physical function; Rehabilitation; rehabilitation exercise; Researchers; Sensors; Tai Ji - methods; Time series; Training; Video Games; Virtual Reality; United States > US; Kinect; exergame; automatic coaching; dynamic time warping; rehabilitation exercise; physical function; aging
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s19132882

Older people face difficulty engaging in conventional rehabilitation exercises for improving physical functions over a long time period due to the passive nature of the conventional exercise, inconvenience, and cost. This study aims to develop and validate a dynamic time warping (DTW) based algorithm for assessing Kinect-enabled home-based physical rehabilitation exercises, in order to support auto-coaching in a virtual gaming environment. A DTW-based algorithm was first applied to compute motion similarity between two time series from an individual user and a virtual coach. We chose eight bone vectors of the human skeleton and body orientation as the input features and proposed a simple but innovative method to further convert the DTW distance to a meaningful performance score in terms of the percentage (0–100%), without training data and experience of experts. The effectiveness of the proposed algorithm was validated through a follow-up experiment with 21 subjects when playing a Tai Chi exergame. Results showed that the algorithm scores had a strong positive linear relationship (r = 0.86) with experts’ ratings and the calibrated algorithm scores were comparable to the gold standard. These findings suggested that the DTW-based algorithm could be effectively used for automatic performance evaluation of an individual when performing home-based rehabilitation exercises.