Design and multichannel electromyography system-based neural network control of a low-cost myoelectric prosthesis hand

Abstract

Abstract. This study introduces a new control method for electromyography (EMG) in a prosthetic hand application with a practical design of the whole system. The hand is controlled by a motor (which regulates a significant part of the hand movement) and a microcontroller\nboard, which is responsible for receiving and analyzing signals acquired by\na Myoware muscle device. The Myoware device accepts muscle signals and sends them to the controller. The controller interprets the received signals\nbased on the designed artificial neural network. In this design, the muscle\nsignals are read and saved in a MATLAB system file. After neural network\nprogram processing by MATLAB, they are then applied online to the prosthetic hand. The obtained signal, i.e., electromyogram, is programmed to control the motion of the prosthetic hand with similar behavior to a real human hand.\nThe designed system is tested on seven individuals at Gaziantep University.\nDue to the sufficient signal of the Mayo armband compared to Myoware sensors, Mayo armband muscle is applied in the proposed system. The discussed results\nhave been shown to be satisfactory in the final proposed system. This system was a feasible, useful, and cost-effective solution for the handless or\namputated individuals. They have used the system in their day-to-day\nactivities that allowed them to move freely, easily, and comfortably.