Identify Arm Motions Using EMG Signals and Deep Learning.

Version 1.0.0 (2.88 KB) by BISHNU
This example employs sequence-to-sequence classification with an LSTM network to detect arm motions from EMG signals, achieving an 84% accu
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Updated 11 Apr 2024

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This example employs sequence-to-sequence classification with an LSTM network to detect arm motions from EMG signals, achieving an 84% accuracy. Misclassifications primarily occurred between hand open and wrist extension, and hand close and wrist flexion, attributed to overlapping muscle activation patterns and electrode placement bias towards muscles involved in wrist flexion.

Cite As

BISHNU (2024). Identify Arm Motions Using EMG Signals and Deep Learning. (https://www.mathworks.com/matlabcentral/fileexchange/163161-identify-arm-motions-using-emg-signals-and-deep-learning), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2024a
Compatible with any release
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Version Published Release Notes
1.0.0