A senior project conducted by Jim Ramsay and Aditya Patel, advised by Dr. Yufeng Lu and Dr. In Soo Ahn.
Sponsored by Bradley University, Department of Electrical and Computer Engineering
Credit to Fernando Cosentino and dzhu for developing the python code upon which this project is based.
Surface Electromyography (EMG) is a non-invasive technique which records the electrical activity of muscles through electrodes placed directly on the arm. This project aims to develop an EMG-based control system. A Myo Armband, containing eight electrode pairs, wirelessly transmits EMG data to a central controller, which runs conditional logic functions to identify three different user hand gestures. The commands are used to remotely pan individual cameras and select from multiple video feeds. Our study demonstrates that EMG-based gesture control is a viable human machine interface option for a variety of applications in the industrial, medical, and consumer markets.
Please refer to our website: http://ee.bradley.edu/projects/proj2018/emg for further explanation of the system, as well as videos of the working project.
Please refer to the setup guide in the documentation folder to see how we configured the three Raspberry Pi computers used in this project.
