DocumentCode :
1239795
Title :
Assistive Control System Using Continuous Myoelectric Signal in Robot-Aided Arm Training for Patients After Stroke
Author :
Song, Rong ; Tong, Kai-Yu ; Hu, Xiaoling ; Li, Le
Author_Institution :
Dept. of Health Technol. & Inf., Hong Kong Polytech. Univ., Kowloon
Volume :
16
Issue :
4
fYear :
2008
Firstpage :
371
Lastpage :
379
Abstract :
In some stroke rehabilitation programs, robotic systems have been used to aid the patient to train. In this study, a myoelectrically controlled robotic system with 1 degree-of-freedom was developed to assist elbow training in a horizontal plane with intention involvement for people after stroke. The system could provide continuous assistance in extension torque, which was proportional to the amplitude of the subject´s electromyographic (EMG) signal from the triceps, and could provide resistive torques during movement. This study investigated the system´s effect on restoring the upper limb functions of eight subjects after chronic stroke in a twenty-session rehabilitation training program. In each session, there were 18 trials comprising different combinations of assistive and resistive torques and an evaluation trial. Each trial consisted of five cycles of repetitive elbow flexion and extension between 90deg and 0deg at a constant velocity of 10deg /s. With the assistive extension torque, subjects could reach a more extended position in the first session. After 20 sessions of training, there were statistically significant improvements in the modified Ashworth scale, Fugl-Meyer scale for shoulder and elbow, motor status scale, elbow extension range, muscle strength, and root mean square error between actual elbow angle and target angle. The results showed that the twenty-session training program improved upper limb functions.
Keywords :
biomechanics; diseases; electromyography; medical computing; medical robotics; patient rehabilitation; Fugl-Meyer scale; assistive control system; continuous myoelectric signal; elbow extension range; elbow flexion; electromyographic signal; extension torque; modified Ashworth scale; motor status scale; muscle strength; resistive torques; robot-aided arm training; stroke rehabilitation; triceps; Arm tracking; arm tracking; myoelectric control; robot-assisted rehabilitation; stroke; Adult; Electromyography; Feedback; Female; Humans; Male; Middle Aged; Movement Disorders; Physical Therapy Modalities; Robotics; Stroke; Therapy, Computer-Assisted; Treatment Outcome;
fLanguage :
English
Journal_Title :
Neural Systems and Rehabilitation Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
1534-4320
Type :
jour
DOI :
10.1109/TNSRE.2008.926707
Filename :
4537156
Link To Document :
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