Pan Lizheng, Zhao Lu, Song Aiguo, Yin Zeming, She Shigang
School of Mechanical Engineering, Changzhou University, Changzhou, China.
Remote Measurement and Control Key Lab of Jiangsu Province, School of Instrument Science and Engineering, Southeast University, Nanjing, China.
Front Robot AI. 2019 Nov 8;6:102. doi: 10.3389/frobt.2019.00102. eCollection 2019.
During robot-aided rehabilitation exercises, monotonous, and repetitive actions can, to the subject, feel tedious and tiring, so improving the subject's motivation and active participation in the training is very important. A novel robot-aided upper limb rehabilitation training system, based on multimodal feedback, is proposed in this investigation. To increase the subject's interest and participation, a friendly graphical user interface and diversiform game-based rehabilitation training tasks incorporating multimodal feedback are designed, to provide the subject with colorful and engaging motor training. During this training, appropriate visual, auditory, and tactile feedback is employed to improve the subject's motivation via multi-sensory incentives relevant to the training performance. This approach is similar to methods applied by physiotherapists to keep the subject focused on motor training tasks. The experimental results verify the effectiveness of the designed multimodal feedback strategy in promoting the subject's participation and motivation.
在机器人辅助康复训练过程中，单调重复的动作对于训练对象来说可能会感到乏味和疲惫，因此提高训练对象的积极性并使其积极参与训练非常重要。本研究提出了一种基于多模态反馈的新型机器人辅助上肢康复训练系统。为了提高训练对象的兴趣和参与度，设计了一个友好的图形用户界面以及包含多模态反馈的多样化游戏式康复训练任务，为训练对象提供丰富多彩且引人入胜的运动训练。在该训练过程中，通过与训练表现相关的多感官激励措施，采用适当的视觉、听觉和触觉反馈来提高训练对象的积极性。这种方法类似于物理治疗师采用的使训练对象专注于运动训练任务的方法。实验结果验证了所设计的多模态反馈策略在促进训练对象参与度和积极性方面的有效性。
