Identification of Motion-Based Action Potentials in Neural Bundles

Abstract

Realizing a nerve signal based prostheses control or limb stimulation is a great challenge in medical technology. It requires a recording and an identification process of the motion-based action potentials of motor and sensory nerves within the corresponding neural bundle. Two additional key factors are used by multi agent-based learning algorithm: The anatomical disposition of the nerves within the neural bundle and the inverse kinematic. In this paper the authors introduce the Smart Modular Biosignal Acquisition, Identification and Control System and its application environment. They present the different process levels and their characteristic identification contribution and they give an overview of the multi-agent based identification framework. The authors show the verification environment and present results regarding the first-level identification procedure.