| 引用本文: | 杨大鹏,赵京东,姜力,刘宏.多抓取模式下人手握力的肌电回归方法[J].哈尔滨工业大学学报,2012,44(1):83.DOI:10.11918/j.issn.0367-6234.2012.01.016 |
| YANG Da-peng,ZHAO Jing-dong,JIANG Li,LIU Hong.Force regression from EMG signals under different grasping patterns[J].Journal of Harbin Institute of Technology,2012,44(1):83.DOI:10.11918/j.issn.0367-6234.2012.01.016 |
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| 摘要: |
| 为实现假手抓取物体时的力控制,采用支持向量机回归算法从多通道肌电信号中实时萃取握力信息.利用6通道表面肌肤电极采集人体前臂肌电信号,采用一枚6维力传感器记录人手施力信息,讨论了随意捏取以及3种规范化捏取模式下两者的回归精度,并进行了跨期次精度验证及多方法比较实验.结果表明,采用支持向量机方法能够获得较好的跨期次回归性能:随意捏模式均方误差(6.31±1.20)N,相关系数平方0.85±0.05;规范化模式均方误差(5.04±0.67)N,相关系数平方0.90±0.03.结合模式分类算法,在线握力回归误差可达5 N左右,误差率在10%以内. |
| 关键词: 假手 肌电 支持向量机 回归 |
| DOI：10.11918/j.issn.0367-6234.2012.01.016 |
| 分类号: |
| 基金项目:国家高技术研究发展计划资助项目(2009AA043803);新世纪优秀人才支持计划(NCET-09-0056);国家重点实验室自主课题(SKLRS200901B);国家基础研究发展规划资助项目(973-2011CB013306;2011CB013305) |
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| Force regression from EMG signals under different grasping patterns |
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YANG Da-peng, ZHAO Jing-dong, JIANG Li, LIU Hong
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State Key Laboratory of Robotics and System,Harbin Institute of Technology,150001 Harbin,China
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| Abstract: |
| To implement the force control of a prosthetic hand when grasping objects,a method of support vector regression(epsilon-SVR) is adopted to extract the force information from multi-channel myoelectric(eletromyography,EMG) signals.Six surface EMG electrodes are attached on the forearm for recording EMG signals.A six-dimensional force sensor is used for collecting the force data.The regression accuracy between these two signals is studied under several hand grasping modes,i.e.,one random grasping mode and three standardized grasping modes.The experimental results show that the epsilon-SVR can achieve better cross-session regression accuracy.Under the random mode,the mean squared error(MSE) is(6.31±1.20)N,and the squared correlation coefficient(SCC) is 0.85±0.05.While under the standardized modes,the mean MSE and SCC can arrive at(5.04±0.67) N and 0.90±0.03,respectively.Companying with pattern recognition,the online force regression can acquire an error around 5 N,which is bellow 10% of the full force range. |
| Key words: prosthetic hand electromyography support vector machine regression |
