A Five-fingered Underactuated Prosthetic Hand System

Abstract

A five-fingered underactuated prosthetic hand controlled by surface EMG (electromyographic) signals is presented in this paper. The prosthetic hand is designed with simplicity, lightweight and dexterity on the requirement of anthropomorphic hands. Underactuated self-adaptive theory is adopted to decrease the number of motors and weight. The fingers of the hand with multi phalanges have the same size as an adult hand. The prosthetic hand control part is based on an EMG motion pattern classifier which combines VLR (variable learning rate) based neural network with wavelet transform and sample entropy. This motion pattern classifier can successfully identify the flexion and extension of the thumb, the index finger and the middle finger, by measuring the EMG signals through three electrodes mounted on the flexor digitorum profundus, flexor pollicis longus and extensor digitorum. Furthermore, via continuously controlling single finger's motion, the five-fingered underactuated prosthetic hand can achieve more prehensile postures such as power grasp. The experimental results show that the system has a great application value