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A senior project conducted by James Ramsay and Aditya Patel, advised by Dr. Yufeng Lu and Dr. In Soo Ahn. Sponsored by Bradley University

Home Page: http://ee.bradley.edu/projects/proj2018/emg

Python 43.49% HTML 50.21% CSS 6.30%
emg myo myo-armband gesture-recognition servo-control human-pose-estimation

2017-2018_emg_senior_project's Introduction

2017-2018 EMG HMI

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.

Abstract

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.

Further Information

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.

Hardware Diagram

Hardware Diagram Please refer to the setup guide in the documentation folder to see how we configured the three Raspberry Pi computers used in this project.

System Flowchart

System Flowchart

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