Active upper limb prosthesis based on natural movement trajectories.

The motion of the current prostheses is sequential and does not allow natural movements. In this work, complex natural motion patterns from a healthy upper limb were characterized in order to be emulated for a trans-humeral prosthesis with three degrees of freedom at the elbow. Firstly, it was necessary to define the prosthesis workspace, which means to establish a relationship using an artificial neural network (ANN), between the arm-forearm (3-D) angles allowed by the prosthesis, and its actuators length. The 3-D angles were measured between the forearm and each axis of the reference system attached at the elbow. Secondly, five activities of daily living (ADLs) were analyzed by means of the elbow flexion (EF), the forearm prono-supination (FPS) and the 3-D angles, from healthy subjects, by using a video-based motion analysis system. The 3-D angles were fed to the prosthesis model (ANN) in order to analyze which ADLs could be emulated by the prosthesis. As a result, a prosthesis kinematics approximation was obtained. In conclusion, in spite of the innovative mechanical configuration of the actuators, it was possible to carry out only three of the five ADLs considered. Future work will include improvement of the mechanical configuration of the prosthesis to have greater range of motion.