Artificial Lower Limb with Myoelectrical Control Based on Support Vector Machine
Artificial Lower Limb with Myoelectrical Control Based on Support Vector Machine
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DOI：
10.1109/wcica.2006.1713839
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发表时间：
2006-10
期刊：
影响因子：
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通讯作者：
Peng Yang;Lingling Chen;Xin Guo;Xitai Wang;Lifeng Li
中科院分区：
文献类型：
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作者：
Peng Yang;Lingling Chen;Xin Guo;Xitai Wang;Lifeng Li
针对假肢和自然步态的可选控制，提出了肌电控制的假肢模型，并讨论了基于支持向量机的识别方法。肌电信号经过预处理和小波包分析后，伴随着肢体的运动而存储。然后利用支持向量机建立模型，找出肌电信号与腿部运动之间的关系。最后，利用膝关节的连续角度控制假肢装置。仿真结果表明，肌电信号与膝关节角度有很强的相关性，该算法取得了较好的预测效果
For the optional control to artificial lower limb and natural gait, an artificial limb model with myoelectrical control was presented, and the recognition method based on support vector machine was discussed. The electromyography signal after pretreating and wavelet packet analyzing was stored in company with the motion of lower limb. Then support vector machine was used to build a model and found the relationship between electromyography signal and motion of leg. Finally, continuous angles of knee joint were used to control artificial limb device. Simulation results show that electromyography signal and angles of knee joint have strong relationship, and this algorithm obtains preferable forecast result