kaviles22/EMG_SignalClassification
Preprocessing and classify EMG signals, using Tensorflow and Tensorflow Lite to deploy an AI model in a ESP32C3
This project helps bioengineers and prosthetics researchers develop and test affordable bionic hands. It takes raw electromyography (EMG) signals from muscle activity as input and processes them to classify motor intentions. The output is a control signal that actuates a 3D-printed hand prosthesis, enabling real-time movement based on detected muscle tasks.
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Use this if you are designing or prototyping low-cost prosthetic limbs and need a complete workflow for EMG signal processing, AI model training, and real-time control deployment on embedded hardware.
Not ideal if you are looking for a commercial, off-the-shelf prosthetic solution or if your primary interest is in advanced, non-EMG based control systems.
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C++
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Last pushed
Sep 06, 2023
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