Development of high-density surface electromyography (HD-sEMG) sensor based on stochastic myo-processor for enhanced human-machine interface

Abstract

With the development of assistive devices, prostheses and rehabilitation robots, researchers have a growing interest in developing the effective Human-Machine Interface (HMI). Surface electromyography (sEMG) signal, which is one of the major neural signals, has been applied to HMI for decades. In previous research, many studies attempt to achieve accurate estimation and consistent force levels from sEMG signals and applied to control robotic devices. In order to quantitively estimate muscle force, inspired by stochastic myo-processor, using multiple-channel sEMG signals is an effective method to increase signal-to-noise ratio (SNR, i.e. the mean of the amplitude estimation divided by standard deviation). Currently, the commercial sEMG sensors are mainly bipolar electrodes as one channel with differential amplification. There are few existing commercial high-density sEMG (HD-sEMG) systems. However, it is impossible to customize the sensor array. In the other hand, the contact position on skin have influence on the performance of the sEMG sensor. In this case, it is possible to achieve robust EMG signal information using HD-sEMG sensor.

In this study, a 16-channel flexible HD-sEMG sensor was developed. In order to finalize design parameters of developed sensor, different prototypes of 1 channel sensors are fabricated to test the effects of the material of electrodes, the size of electrodes, and the internal electrode distance (IED) in terms of SNR and the skin impedance. After the detailed test of 1-channel sensor, the design parameters were selected and expanded to the HD-sEMG sensor. Finally, a torque estimation experiment was conducted with the designed HD-sEMG sensor and stochastic myo-processor algorithm. The results indicate the 16-channel HD-sEMG sensor effectively improved the estimation accuracy than using one sEMG sensor. For further application, the proposed HD-sEMG sensor can be used as an enhanced human-machine interface to achieve robust control of robotics devices, such as exoskeleton, prosthesis and rehabilitation robot.