Body activity grading strategy for cervical rehabilitation training

Liang Dong and Yun Qu

Computer Methods in Biomechanics and Biomedical Engineering, 2023, vol. 26, issue 12, 1489-1498

Abstract: A body activity grading strategy is proposed for computer-assisted cervical rehabilitation training, which employs hidden Markov model to partition an exercise into independently assessable phases and a scoring reference to rate respective kinematic features. Samples of 34 cervical rehabilitation exercises are evaluated by both manual and the proposed approaches, where the average phase segmentation difference is 93 ms, the phase scoring difference is 0.045, and the grading difference for overall samples is 5.5% between the approaches. It indicates that the proposed method has similar accuracy as physical therapists and is thus capable of performing online supervision for cervical rehabilitation training.

Date: 2023
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DOI: 10.1080/10255842.2022.2122820

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