摘要
目的设计并实现基于表面肌电信号的4种手腕动作意图的在线自动识别,为基于生物电信号的控制系统提供一种可行的人机交互方式。方法采集受试者4种手腕翻转动作时,人体上肢3处肌肉群的表面肌电信号。计算肌电信号特征,并与初始化阶段设定的阈值相比较,获得特征参数的二值化处理结果,根据三通道肌电二值化结果的逻辑识别组合,实现4种手腕翻转动作意图的在线识别。结果通过10名受试者的在线测试,识别准确率接近100%。结论提出的动作意图识别方法,具有良好的在线处理性能,方法简单且易实现,所提取的手腕动作意图可转换成不同的控制命令,能够提供一种有效可行的基于生物电信号的人机交互模式。
Objective An automatic on-line algorithm for motion intention recognition of wrist movements based on surface eleotromyography （sEMG） was proposed. The ultimate purpose is to realize a usable human machine interaction for biomedical control systems. Methods Three channels of sEMG signals are recorded when the subject is doing four kinds of wrist turning gestures. The EMG parameter is compared with a threshold which is determined during the initial stage. The obtained comparison results are binary values. According to the designed recognition logic, the motion intention of wrist movement is extracted automatically. Results Totally,ten subjects are participated in the experiment and the recognition accuracy is near to 100%. Conclusions The proposed movement intention recognition method has good performance for online EMG processing,and is simple and easy to be realized. The obtained motion intention is usable for further control purposes to realize an effective biomedical signal-based human machine interaction.
出处
《北京生物医学工程》
2013年第5期467-471,484,共6页
Beijing Biomedical Engineering
基金
上海市科委科技创新行动计划产学研医合作项目(12DZ1940903)
上海市大学生创新性实验计划(S11069)资助
关键词
表面肌电信号
手腕动作
动作意图
人机交互
surface eleotromyography
wrist movement
motion intention
human machine interaction
