Abstract

Capture and utility of neurophysical signals through non-invasive techniques can provide valuable insight into properties of the nervous system and physical response to external stimuli. Electromyography (EMG) is an electrophysiologic test that measures muscle response and electrical activity. This project aims to utilize real-time processing of EMG signals from the wrist and translate captured features into controls. A potential application is replacing the remote control of an electric skateboards, which could be attached to a smartwatch and is more intuitive to use. This project addresses the design and fabrication of a circuit board with ideal amplification and filter values to capture EMG, a wristband to house the system in a consumer wearable device, software to process and classify features within the signal, and a smartphone app for managing the device and connecting it to external peripherals.

RobLES