Reducing Compensatory Motions in Motion-Based Video Games for Stroke Rehabilitation

Stroke survivors’ unsupervised therapeutic exercise motions are often accompanied by harmful compensatory motions that prevent proper motor recovery and introduce additional health issues. These compensatory motions are often performed unconsciously and are difficult to prevent. Motion-based games show promise for motivating patients to perform stroke rehabilitation exercises at home by themselves. Currently, exercises with these games are likely to contain undesired compensatory motions. In this article, we provide the design and empirical evaluation of a motion-based game system that addresses the issue of compensation in therapeutic games. We introduce a technique to identify and measure compensation, develop a game that meaningfully uses exercise and compensation as inputs, and use incentives and disincentives to reduce compensation. We show that this technique outperforms existing approaches by significantly reducing compensatory motions during therapeutic exercise. This has important implications for therapeutic games, which can use our findings to improve the quality of motions to be closer to therapist-supervised motions. Our techniques can increase the effectiveness of therapeutic games and reduce the possibility that they may cause harm in long-term use.

脑卒中幸存者在无监督康复训练中的运动动作，常伴随有害的代偿动作（compensatory motions）——这类动作不仅会阻碍正常的运动功能恢复，还会引发额外的健康问题。这类代偿动作往往在无意识间完成，且难以主动规避。基于动作捕捉的游戏（motion-based games）有望激励患者自主在家开展脑卒中康复训练，但当前这类游戏配套的训练动作，仍大概率出现非预期的代偿动作。针对康复游戏中的代偿动作问题，本文提出并完成了一款基于动作捕捉的游戏系统的设计与实证评估。我们研发了一套可识别并量化代偿动作的技术，设计了一款将训练动作与代偿动作同时作为有效输入的游戏，并通过奖惩机制降低代偿动作的发生率。实验结果表明，相较于现有方案，本技术可显著降低康复训练中的代偿动作占比。该成果对康复游戏领域具有重要借鉴价值：相关研究可依托本研究结论优化训练动作质量，使其更接近治疗师现场监督下的标准动作。本技术可有效提升康复游戏的训练效果，同时降低其长期使用过程中引发健康风险的可能性。