Real-Time and Simultaneous Control of Artificial Limbs Based on Pattern Recognition Algorithms

The prediction of simultaneous limb motions, e.g. moving two fingers at the same time, is a highly desirable feature for the control of artificial limbs. We investigate different control strategies for both individual and simultaneous movements using muscle signals acquired from able-bodied participants. Our proposed controller based on a neural network outperformed the state-of the-art and allowed the simultaneous control of three different hand movements.