Myographic System of the Bionic Wrist with Surface Type Identification

This chapter presents the creation features of a myographic system for the prosthetic wrist with advanced movement and gesture capabilities. The system is based on recognizing myoelectric signals by a neural network interface and using an optical identifier to detect the contact surface of the fingers. The coordination of prosthesis movement is achieved through simultaneous registration and recognition of physiological and optical signals. The method of recognizing categories of physiological movements is presented, which involves analyzing electro- and force-myographic signals based on theoretical and experimental features of multilevel artificial neural networks. Additionally, a method of recognizing the contact surface by a prosthesis finger with an optical energy mirror concentrator is shown, which increases the identification reliability of the manipulation object's structure. Lastly, methods improvements for hand prosthesis movement coordination are discussed based on simultaneous registration and recognition of physiological and optical identification signals.