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Processing and Analysis of EMG Signals from MYO Armband for Upper-Limb Prosthesis Control
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Processing and Analysis of EMG Signals from MYO Armband for Upper-Limb Prosthesis Control
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Journal Article
Processing and Analysis of EMG Signals from MYO Armband for Upper-Limb Prosthesis Control
2025
Overview
This paper presents the development of an electromyographic (EMG) signal processing system for controlling upper limb prostheses using data from the MYO Armband, which includes eight EMG sensors. The system processes raw EMG signals through filtering, frequency analysis, and other enhancement techniques to improve signal quality. An interactive MATLAB interface, built on the Myo SDK MATLAB MEX Wrapper, enables real-time visualization and application of various filters. A comprehensive comparison of filtering methods assesses their influence on signal reliability and performance. Quantitative results indicate that the Power Grip gesture produces the highest EMG activation, while the Extended Index Finger shows lower muscle engagement, highlighting distinct activation patterns. Heat map visualizations reveal spatial activation differences across sensors, essential for designing effective gesture classifiers. The developed platform enhances noise robustness and improves accuracy in interpreting motor commands. Despite hardware limitations, the system demonstrates the feasibility of adaptive prosthesis control and suggests integration with hybrid methods, such as voice control, to further enhance functionality and user experience.
Publisher
Bulgarska Akademiya na Naukite / Bulgarian Academy of Sciences,Bulgarian Academy of Sciences
