Abstract Myoelectric Control with an Arduino-based System

Hancong Wu, Sigrid Dupan, Kianoush Nazarpour

Research output: Chapter in Book/Report/Conference proceedingConference contribution


This paper presents the design and evaluation of an Arduino-based system for electromyogram (EMG) signal measurement and prosthesis control with the abstract decoder. It achieves a 2 kHz sampling rate for two EMG channels, processes EMG signals on-the-fly and sends the prosthesis control command via a CAN bus. We tested the accuracy and responsiveness of the system in real-time by playing back previously recorded EMG signals through a Tip, Ring, and Sleeve (TRS) function generator. The correlation coefficients between the mean absolute value (MAV) of the original signals and the measured signals were above 97%.
Original languageEnglish
Title of host publicationMEC20 Symposium Proceedings
Number of pages4
Publication statusPublished - 23 Jul 2020
EventMyoelectric Controls Symposium 2020 - Fredericton, Canada
Duration: 10 Aug 202013 Aug 2020


SymposiumMyoelectric Controls Symposium 2020
Abbreviated titleMEC 2020
Internet address


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