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Detection of Readiness Potential for Lower Limb Voluntary Movement Based on EMG Onset

Hanzhe Li, Xiaodong Zhang, Zhufeng Lu, Rui Li

Year
2019
Citations
2

Abstract

Exoskeleton robots have considerable progress and development. However, there is a problem of incompliant control causing by the time lag between the human movement and the robot's response in lower limb exoskeleton robot system. Combining BCI with exoskeleton robot is an effective way to solve this problem, hence a detection of readiness potential (RP) for lower limb voluntary movement based on EMG onset is proposed in this paper. In this work, the detection system of simultaneous acquisition electroencephalogram (EEG) and electromyography (EMG) for lower limb voluntary movement was constructed and five healthy subjects were recruited in this experiments. Firstly, mechanism of EEG and EMG ware analyzed, EEG and EMG ware excited by the same movement intention. So that, the EMG was used to detect the onset trigger of lower limb voluntary movement based on the proposed method. Then, the onset trigger was marked on EEG for event alignment and segmentation of EEG data. Finally, RP was extracted from EEG based on superposed average method. The experimental results demonstrated that the variability of the onset trigger was significantly detected; the single and averaged RP were observed in lower limb voluntary movement. Specifically, the RP from FCz, FC1, FC2, C1, C2, CP1, CP2 and Cz were obvious during right leg voluntary movement. But only FCz and FC1 that had a significant RP response during left leg voluntary movement. This work demonstrates that the proposed method can detect the RP for lower limb voluntary movement, thus it can provide advance information for compliant control of lower limb exoskeleton robot.

Keywords

ExoskeletonElectroencephalographyElectromyographyPhysical medicine and rehabilitationWork (physics)Computer scienceMovement (music)Lower limbSimulationArtificial intelligence

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