Design and Control of an EMG-based Low-cost Exoskeleton for Stroke Rehabilitation

被引:0
作者
Asokan, Anand [1 ]
Vigneshwar, M. [2 ]
机构
[1] Natl Inst Technol Tiruchirappalli, Dept Instrumentat & Control Engn, Tiruchirappalli 620015, Tamil Nadu, India
[2] Natl Inst Technol Tiruchirappalli, Dept Elect & Commun Engn, Tiruchirappalli 620015, Tamil Nadu, India
来源
2019 FIFTH INDIAN CONTROL CONFERENCE (ICC) | 2019年
关键词
Electromyography (EMG); Rehabilitation; Post-stroke care; Exoskeleton; Robotics;
D O I
10.1109/indiancc.2019.8715555
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Rehabilitation of patients who have recovered from a stroke is a tedious and difficult process, involving a very long recovery time for the patient. Therapists guide patients to do a series of exercises or tasks, for short but intensive sessions. Passive exoskeletons are often used to keep track of the patient's progress digitally, along with therapist supervision. In any case, it is an expensive and slow process, since the sessions are very short, and trained manpower is required. In this paper, we present the design and control of an active upper limb exoskeleton to address these issues. The exoskeleton is controlled using the EMG signals from the muscle groups involved in the motion, and provides physical assistance to the desired motion. Patients with very limited ability can use preset functions in the exoskeleton, and once they have gained enough muscle strength, they can begin to use the EMG based control. Wearing it over the entire course of the day can perform a dual function of assisting them in their day to day tasks, and performing therapy at the same time. The design of a 1-DoF active exoskeleton, its control, and various modes of operation are presented. The use of EMG signals for control of the exoskeleton is found to be a better option compared to the existing methods.
引用
收藏
页码:478 / 483
页数:6
相关论文
共 14 条
[1]  
[Anonymous], 2017, STROKE REHABILITATIO
[2]  
[Anonymous], 2006, PANASONIC NEWSR 0925
[3]   Optimising engagement for stroke rehabilitation using serious games [J].
Burke, J. W. ;
McNeill, M. D. J. ;
Charles, D. K. ;
Morrow, P. J. ;
Crosbie, J. H. ;
McDonough, S. M. .
VISUAL COMPUTER, 2009, 25 (12) :1085-1099
[4]   Application of EMG signals for controlling exoskeleton robots [J].
Fleischer, Christian ;
Wege, Andreas ;
Kondak, Konstantin ;
Hommel, Guenter .
BIOMEDIZINISCHE TECHNIK, 2006, 51 (5-6) :314-319
[5]   Assessment of an active industrial exoskeleton to aid dynamic lifting and lowering manual handling tasks [J].
Huysamen, Kirsten ;
de Looze, Michiel ;
Bosch, Tim ;
Ortiz, Jesus ;
Toxiri, Stefano ;
O'Sullivan, Leonard W. .
APPLIED ERGONOMICS, 2018, 68 :125-131
[6]  
Jamal M.Z., 2012, Computational Intelligence in Electromyography Analysis - A Perspective on Current Applications and Future Challenges, P427, DOI [DOI 10.5772/52556, 10.5772/52556]
[7]   A Novel Hybrid Rehabilitation Robot for Upper and Lower Limbs Rehabilitation Training [J].
Khor, K. X. ;
Rahman, H. A. ;
Fu, S. K. ;
Sim, L. S. ;
Yeong, C. F. ;
Su, E. L. M. .
MEDICAL AND REHABILITATION ROBOTICS AND INSTRUMENTATION (MRRI2013), 2014, 42 :293-300
[8]   An upper-body rehabilitation exoskeleton Harmony with an anatomical shoulder mechanism: Design, modeling, control, and performance evaluation [J].
Kim, Bongsu ;
Deshpande, Ashish D. .
INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH, 2017, 36 (04) :414-435
[9]   Stroke Care 2 Stroke rehabilitation [J].
Langhorne, Peter ;
Bernhardt, Julie ;
Kwakkel, Gert .
LANCET, 2011, 377 (9778) :1693-1702
[10]  
Özgünen KT, 2010, J SPORT SCI MED, V9, P620