A Novel Robot-Aided Upper Limb Rehabilitation Training System Based on Multimodal Feedback

Lizheng Pan; Lu Zhao; Aiguo Song; Zeming Yin; Shigang She

doi:10.3389/frobt.2019.00102

A Novel Robot-Aided Upper Limb Rehabilitation Training System Based on Multimodal Feedback

Front Robot AI. 2019 Nov 8:6:102. doi: 10.3389/frobt.2019.00102. eCollection 2019.

Authors

Lizheng Pan^{1

2}, Lu Zhao¹, Aiguo Song², Zeming Yin¹, Shigang She¹

Affiliations

¹ School of Mechanical Engineering, Changzhou University, Changzhou, China.
² Remote Measurement and Control Key Lab of Jiangsu Province, School of Instrument Science and Engineering, Southeast University, Nanjing, China.

Abstract

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.

Keywords: motion training; multimodal feedback; rehabilitation robot; stroke; upper limb.