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Bionic-prosthesis-on-AI

Real-time EMG signal classification for the bionic prosthesis design

The final demonstration of the project is shown in the following link: https://drive.google.com/file/d/1NqWnGPf58lklonyfdcCDBk1DoelbOwiD/view.

The code is written to classify 5 hand gestures + rest position using the Support Vector Machine (SVM) classifier based on the time-domain (TD) features extracted from the denoised EMG signals. The EMG signals have been recorded using 5 muscle sensors with gelled pads all connected to the Arduino Uno board for transmission of signals to the laptop.

The SVM model has been first trained in 8+ sessions, where in each session there were 10 repetitions for each of the gesture. Lastly, the real-time prediction is run using the buffer of 32 samples.

Feel free to ask any further questions by writing to my email: daniyar.zhakyp@nu.edu.kz