DOI: 10.36347/sjet

Pages: 252-257

Electromyography (EMG) is a technique used to record the electrical activity of skeletal muscles. Through EMG, many signals can be obtained from the body, evaluated by signal processing, and then utilized in various applications. Currently, noninvasive EMG methods are being used to control some of the world’s most advanced prosthetic devices, in addition to help in the field of robotic rehabilitation. This paper proposes a useful, low-cost method for controlling an individual finger movement of a robotic hand through the use of surface EMG (sEMG) signal acquisition from the human forearm. During this project, EMG signals were extracted from five muscles of the forearm via surface electrodes. These signals were amplified up to 4V maximum, filtered using second-order band pass filter of 20-1000 Hz, and rectified through a designed analog integrated circuits. Then the signals were converted to the digital form with the use of 10 bit analog-to-digital converter within the Arduino™microcontroller board. From here, the signals were implemented into a Simulink®model that used fast fourier transform (FFT), root mean square (RMS), and thresholding techniques to determine changes in the signal in order to generate Pulse-Width Modulation (PWM) for the five Futaba®S3114 micro servos of the Mecha TE™ Hand. After analysis of the data and project results, it was concluded that a method of using sEMG signal acquisition for robotic hand control in real time has been attained. Current setup can also be used with virtual hand control using Matlab 3D Animation toolbox.