Real time tracking algorithm of sEMG-based human arm motion

Abstract

This paper suggests the real time tracking algorithm for human arm motion by processing the signals of surface EMG (ElectroMyoGram) sensors attached on both upper arm and shoulder. The signals acquired by using surface EMG sensors are processed with choosing the maximum in a short period, taking the absolute value, and filtering noises out with a low-pass filter. The processed signals are directly used for the motion generation of virtual arm in real time simulator. The virtual arm of simulator has two degrees of freedom and complies with the desired flexion/extension motions of both the elbow and shoulder of human. Also, we show the validity of the suggested algorithms through the experimental results.