Research on gait recognition of lower limb exoskeleton robot based on sEMG&IMU feature fusion.

Aiming at the problems of low accuracy and poor robustness in gait recognition of lower extremity exoskeleton robots in human-computer interaction, a depth residual contraction network recognition method based on the fusion of surface electrosemg (sEMG) and inertial measurement unit (IMU) signals was proposed. Firstly, a new energy kernel feature extraction method was used to extract sEMG signals. Based on the sEMG oscillator model, the sEMG energy kernel phase diagram was converted to gray level map by matrix counting method.