Development of intuitive human-machine interface based on Electromyography for assistive robot (KAAD)

This paper describes the development of hardware and software of Human-Machine Interface (HMI) for active assistive device based on surface Electromyography signals (sEMG). The sEMG signals have been chosen as the most intuitive and transparent source of information on detection of users intention. For work presented in this paper, our research activities focus mainly on development of hardware, algorithms and methods for muscle Torque/Force estimation and muscle fatigue detection suited for embedded devices. The HMI hardware has been custom designed to our KAAD system frame and is equipped with interfaces allowing it to exchange data with other components of our assistive device. Preliminary results for muscle force/torque estimation and muscle fatigue level are also presented.