Affiliations: Institute of Rehabilitation Engineering and Technology, University of Shanghai for Science and Technology, Shanghai, China
Correspondence:
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Corresponding author: Ping Shi, Institute of Rehabilitation Engineering and Technology, University of Shanghai for Science and Technology, Shanghai, China. E-mail: pshi@usst.edu.cn.
Abstract: BACKGROUND: At present, the popular control method for intelligent bionic prosthetic hands is EMG control. However, the control accuracy of this method is low. It is a trend to integrate computer vision into the prosthetic hand. OBJECTIVE: The purpose of this paper is to design an intelligent prosthetic hand based on image recognition, improve the control accuracy and the quality of life of the disabled. METHODS: Convolutional neural network is used to recognize the object to be grasped, and the recognition result is used as a trigger signal to control our intelligent prosthetic hand. We have designed a four-bar linkage mechanism and a side swing mechanism in the structure, which can not only achieve the flexion and extension of fingers but also realize the adduction and abduction of the four fingers and the lateral swing of the thumb. RESULTS: Through the method of image recognition, the new intelligent bionic hand can achieve five kinds of Human action. Including grasp, side pinch, three-finger pinch, two-finger pinch, and pinch between fingers. CONCLUSIONS: The experiment result proves that the precision of image recognition control is very excellent, the intelligent prosthetic hand can be completed the corresponding task.
Keywords: Deformable convolution, image recognition, prosthetic hand
