TY - GEN
T1 - Classification of upper limb motions in stroke using high density surface EMG
AU - Zhang, Xu
AU - Zhou, Ping
PY - 2011
Y1 - 2011
N2 - Myoelectric pattern recognition techniques have been developed to infer user's intention of performing different functional movements, which can be used to provide volitional control of assisted devices for people with disabilities. The pattern recognition based myoelectric control systems have rarely been designed for stroke survivors. Aiming at developing such a system for stroke rehabilitation, this study assessed the myoelectric control information remained in the affected limb of stroke survivors using high density surface electromyogram (EMG) recording and pattern recognition techniques. The experimental results from 3 stroke subjects indicate that high accuracies (92.42% ± 5.51%) can be achieved in classification of 20 different intended movements of the affected limb. This study confirms that substantial motor control command can be extracted from paretic muscles of stroke survivors, potentially facilitating their rehabilitation.
AB - Myoelectric pattern recognition techniques have been developed to infer user's intention of performing different functional movements, which can be used to provide volitional control of assisted devices for people with disabilities. The pattern recognition based myoelectric control systems have rarely been designed for stroke survivors. Aiming at developing such a system for stroke rehabilitation, this study assessed the myoelectric control information remained in the affected limb of stroke survivors using high density surface electromyogram (EMG) recording and pattern recognition techniques. The experimental results from 3 stroke subjects indicate that high accuracies (92.42% ± 5.51%) can be achieved in classification of 20 different intended movements of the affected limb. This study confirms that substantial motor control command can be extracted from paretic muscles of stroke survivors, potentially facilitating their rehabilitation.
UR - https://www.scopus.com/pages/publications/84862619037
U2 - 10.1109/IEMBS.2011.6090912
DO - 10.1109/IEMBS.2011.6090912
M3 - 会议稿件
C2 - 22255061
AN - SCOPUS:84862619037
SN - 9781424441211
T3 - Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
SP - 3367
EP - 3370
BT - 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011
T2 - 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011
Y2 - 30 August 2011 through 3 September 2011
ER -