摘要
为解决多自由度假手肌电控制难题,建立一种人手预抓取模式的在线识别方法,并将其应用至HIT-DLR假手的抓取控制。基于Teager-Kaiser能量算子增幅肌电信号在肌肉动作发起时的变化,引入后处理解决噪声影响,提出一种预抓取发起的在线检测方法。针对人手4种预抓取模式,讨论不同肌电信号分段方法,不同时域特征、频域特征和时频域特征以及多种分类方法所能获得的识别成功率。最终建立了基于波形长度及支持矢量机的最优识别方法,成功率可达95%,延迟小于300 ms。肌电控制试验表明,假手可以准确快速地抓取各种不同形状的物体。
It appears a big challenge when the multi-DOFs prosthetic hand is controlled by the electromyography （EMG） signals. A novel recognition method of the hand grasp preshaping patterns is proposed to the HIT-DLR prosthetic hand＇s EMG control. A new online detection method is designed to collect the accurate onset EMG signals of the grasp preshaping, which uses the Teager-Kaiser energy （TKE） operator and post processing to enlarge the changes of the EMG signal and deal with the spike noise, respectively. Focusing on 4 types of the hand preshaping patterns, different data segmentation methods, different features coming from the time-domain, frequency domain and time-frequency domain, and various classifiers are attempted to find the best classification accuracy. The waveform length and support vector machine are chosen, which can reach an accuracy of 95% and a response time less than 300 ms. The experiment of the prosthetic hand control shows that the hand can swiftly grasp the objects with various shapes.
出处
《机械工程学报》
EI
CAS
CSCD
北大核心
2012年第15期1-8,共8页
Journal of Mechanical Engineering
基金
国家重点基础研究发展计划(973计划
2011CB013306
2011CB013305)
国家自然科学基金(51175106
60775060)
机器人技术与系统国家重点实验室自主研究课题(SKLRS201201A03)资助项目
关键词
假手
肌电控制
预抓取
模式识别
Prosthetic hand ，Electromyography control， Grasp preshaping ，Pattern recognition
