基于表面肌电和组织阻抗信息融合的手势识别研究

The Study of Hand Gesture Recognition Based on the Fusion of Surface Electromyography and Tissue Impedance

手势识别中的一种常见方式是通过表面肌电信号来实现。为提高手势识别的稳定性和精度,通常需要采集多个通道的肌电信号,但这会增加电极传感器的数量以及识别系统的复杂度。因此,如何利用较少量的通道采集信号并确保手势识别的性能一直是肌电信号应用到意图识别的研究方向之一。该研究设计了一款便携式四通道肌电和阻抗双模信号采集器,在不增加额外传感器和通道数的情况下,能同时采集肌电信号和差分电极对之间的组织阻抗信号。初步实验结果表明,通过该系统采集的四通道融合信息可以提升手势识别的准确率和稳定性。与仅采集肌电信息相比,该研究采用的肌电与阻抗信息融合方法可以将手势识别性能提升3%以上,达到96.2%的识别率。

Using surface electromyography(sEMG)signals to gesture recognition is a common method.In order to improve the stability and accuracy of gesture recognition,it usually requires to collect more channels of myoelectric signals.However,this would need a high number of electrodes,resulting the increasing of the complexity of myoelectric recognition system.Therefore,using a small number of sEMG electrodes to ensure the performance of gesture recognition has always been an promising direction in the sEMG-based applications.In this study,we designed a portable four-channel sEMG and impedance signal acquisition device that can simultaneously collect sEMG and tissue impedance signal between differential electrode pairs without adding additional sensors and channels.The self-made device was used to collect the hybrid signals of sEMG and tissue impedance for seven classes of hand gesture recognition.The experimental results show that the four-channel fusion information collected by the system could improve the accuracy and stability of gesture recognition.Compared with using EMG only,the fusion method could improve gesture recognition performance by more than 3%and achieve a recognition rate of 96.2%.