Synergistic control of forearm based on accelerometer data and artificial neural networks

Abstract

In the present study, we modeled a reaching task as a two-link mechanism. The upper arm and forearm motion trajectories during vertical arm movements were estimated from the measured angular accelerations with dual-axis accelerometers. A data set of reaching synergies from able-bodied individuals was used to train a radial basis function artificial neural network with upper arm/ forearm tangential angular accelerations. The trained radial basis function artificial neural network for the specific movements pred…