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	Pattern recognition based forearm motion classification for patients with chronic hemiparesis
	Geng, Yanjuan; Zhang, Liangqing; Tang, Dan; Zhang, Xiufeng; Li, Guanglin
	2013
会议名称	2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013
会议地点	Osaka, Japan
英文摘要	To make full use of electromyography (EMG) that contains rich information of muscular activities in active rehabilitation for motor hemiparetic patients, a couple of recent studies have explored the feasibility of applying pattern recognition technique to the classification of multiple motion classes for stroke survivors and reported some promising results. However, it still remains unclear if kinematics signals could also bring good motion classification performance, particularly for patients after traumatic brain damage. In this study, the kinematics signals was used for motion classification analysis in three stroke survivors and two patients after traumatic brain injury, and compared with EMG. The results showed that an average classification error of 7.9±6.8% for the affected arm over all subjects could be achieved with a linear classifier when they performed multiple fine movements, 7.9% lower than that when using EMG. With either kind of signals, the motor control ability of the affected arm degraded significantly in comparison to the intact side. The preliminary results suggested the great promise of kinematics information as well as the biological signals in detecting user's conscious effort for robot-aided active rehabilitation.
收录类别	EI
语种	英语
内容类型	会议论文
源URL	[http://ir.siat.ac.cn:8080/handle/172644/4943]
专题	深圳先进技术研究院_医工所
作者单位	2013
推荐引用方式 GB/T 7714	Geng, Yanjuan,Zhang, Liangqing,Tang, Dan,et al. Pattern recognition based forearm motion classification for patients with chronic hemiparesis[C]. 见:2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013. Osaka, Japan.

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