论文:2019,Vol:37,Issue(3):509-514
引用本文:
张磊, 王文东, 史仪凯, 刘佳豪, 褚阳, 明杏. 肌电信号的离散运动预测研究[J]. 西北工业大学学报
ZHANG Lei, WANG Wendong, SHI Yikai, LIU Jiahao, CHU Yang, Ming Xing. Discrete Motion Prediction Based on EMG Signals[J]. Northwestern polytechnical university

肌电信号的离散运动预测研究
张磊, 王文东, 史仪凯, 刘佳豪, 褚阳, 明杏
西北工业大学 机电学院, 陕西 西安 710072
摘要:
目前的康复训练设备大都体积庞大,响应迟缓。针对这一现状设计了一套便携式三自由度上肢外骨骼机械臂及其控制系统。该机械臂的3个自由度分别是手掌腕部摆动、前臂侧向运动和肘关节转动。对肱二头肌和肱三头肌的肌电信号进行采集,然后对采集的肌电信号进行滤波,提取特征值,以期获得反映人体运动意图的有效信息。在此基础上设计了利用肌电信号实现肘关节转动的离散运动控制方法。实验表明设计的离散运动控制方法平均模式识别正确率能达到90%以上。
关键词:    肌电信号    三自由度    肘关节    离散运动控制模式   
Discrete Motion Prediction Based on EMG Signals
ZHANG Lei, WANG Wendong, SHI Yikai, LIU Jiahao, CHU Yang, Ming Xing
School of Mechanical Engineering, Northwestern Polytechnical University, Xi'an 710072, China
Abstract:
Most of the current rehabilitation equipment is bulky and slow to respond. Therefore, we designed a portable three-degree-of-freedom exoskeleton and discrete-mode control system for this situation. The three degrees of freedom of the exoskeleton robot arm was the wrist swing, the forearm lateral movement, and the elbow rotation. We collected the EMG signals of the biceps and triceps, then filtered the acquired EMG signals and extracted features in order to obtain effective information that reflected the activity intentions. Based on this, a discrete motion control method using the EMG signals to achieve elbow rotation was designed. Experiment suggests that the average pattern recognition accuracy rate can reach more than 90%.
Key words:    EMG signal    three degrees of freedom    elbow joint    discrete motion control mode   
收稿日期: 2018-07-13     修回日期:
DOI: 10.1051/jnwpu/20193730509
基金项目: 陕西省自然科学基金(2018JM5107)资助
通讯作者:     Email:
作者简介: 张磊(1986-),西北工业大学博士研究生,主要从事生物电研究。
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