Electromyography-controlled gamified exercise system for the distal upper extremity: a usability assessment in subacute post-stroke patients

Disability and rehabilitation. Assistive technology(2023)

引用 3|浏览8
暂无评分
摘要
Purpose Movement repetition is known to play a key role in promoting functional improvements or maintaining functional levels in post-stroke hemiparetic patients. However, repetitive movements tend to be monotonous, making it challenging for patients to continue. Here, we developed a new gamified system to allow patients perform repetitive movements with enjoyment. The present study aimed to examine the usability of the system in subacute stroke patients. Method The exercise system comprised an electromyography-controlled operating system that enabled users to play a virtual game by repetitive finger and wrist movements on the affected side. A total of 13 patients with upper-limb hemiparesis underwent a single bout of exercise using the system and assessed its usability, satisfactoriness, enjoyability, etc. using the System Usability Scale (SUS), Quebec User Evaluation of Satisfaction with assistive Technology (QUEST)-like questionnaire, and numerical rating scale (NRS). Results All the participants, who had a wide range of paretic levels, were able to perform the exercise using the system. Participants scored the system a median of 85.0 for SUS and 4.2 for the QUEST-like questionnaire, with an "excellent" in usability and "satisfied" in user satisfaction with the system. The median NRS scores for enjoyability, potential for continuous use, and effectiveness were 8.0, 9.0, and 9.0, respectively, which were greater than the scores for usual rehabilitation training for the upper extremity. Conclusions The novel electromyography-controlled gamified exercise system may have sufficient usability and enjoyability to motivate patients with a wide range of paretic levels to perform repetitive finger and wrist movements.
更多
查看译文
关键词
Gamified rehabilitation,electromyography,usability,satisfaction,enjoyment,stroke,motivation
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要