Physiology-sensitive Virtual Reality based Strength Training Platform for Post-stroke Grip Task

被引:1
作者
Dash, Adyasha [1 ]
Yadav, Anand [1 ]
Lahiri, Uttama [1 ]
机构
[1] Indian Inst Technol Gandhinagar, Elect Engn, Gandhinagar, India
来源
2019 IEEE EMBS INTERNATIONAL CONFERENCE ON BIOMEDICAL & HEALTH INFORMATICS (BHI) | 2019年
关键词
Grip-Task; Virtual-Reality; Surface-Electromyogram; Rehabilitation; Stroke; ELECTROMYOGRAPHIC BIOFEEDBACK; HAND REHABILITATION;
D O I
10.1109/bhi.2019.8834642
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Post-stroke patients often suffer from deficit in grip strength adversely affecting their independent execution of activities of daily living. Although conventional rehabilitation facilitated by expert therapists can address such deficits, in developing countries like India, with low doctor patient ratio such therapist-mediated rehabilitation services often remain inaccessible to many. Thus, investigators have been exploring technology-assisted alternatives e.g., robot and computer-based platforms for rehabilitation. Computer-based systems using Virtual Reality (VR) coupled with peripheral devices are advantageous in terms of their controllability, real-time feedback facility, safety, etc. Additionally, these systems coupled with surface electromyogram (sEMG) based biofeedback can administer muscle strengthening exercises by providing audio-visual representation of muscle activation in VR. In our present work, we have developed a VR-based rehabilitation platform augmented with sEMG-based biofeedback for grip strength training. Results of our study with 6 healthy and 6 post-stroke participants show the potential of our platform to be accepted by both the groups. Additionally, multiple exposures (over 3 weeks) indicate the potential of our system to increase the grip strength of post-stroke patients with increased upper limb muscle activation and improvement in one's functional recovery measured through physiological indicator (Electrodermal activity).
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页数:4
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