Predicting the intended motion with EMG signals for an exoskeleton orthosis controller

In this paper, we present a method to calculate the intended motion of joints in the human body by analysing EMG signals. Those signals are emitted by the muscles attached to the adjoining bones during their activation. With the resulting intended motion, a leg orthosis can be controlled in realtime to support disabled people while walking or climbing stairs and help patients suffering from the effects of a stroke in their rehabilitation efforts. To allow a variety of different motions, a human body model with physical properties is developed and synchronized with data recorded from the pose sensors. Computing the intended motion is performed by converting calibrated EMG signals to muscle forces which animate the model. The algorithm was evaluated with experiments showing the calculated intended motion while climbing one step of a stair. The algorithm and the experimental results are both shown.