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

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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.
Publisher
MDPI
Issue Date
2019-07
Language
English
Article Type
Article
Citation

SENSORS, v.19, no.13, pp.1 - 17

ISSN
1424-8220
DOI
10.3390/s19132882
URI
http://hdl.handle.net/10203/264274
Appears in Collection
IE-Journal Papers(저널논문)
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