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Myoelectric Prosthetic Hand using sEMG and flex sensors

Year: 2016
Tags: Signal Processing, Machine Learning


EMG techniques are popular for prediction of amputated body parts. We used a runtime technique called dynamic time warping for detection of 5 classified hand gestures. Miniaturized sEMG (surface electromyography) electrodes were developed and EMG(electromyography) detection was performed over the forearm. The algorithm was implemented on STM32F4o7 while outputs were observed on a 3D printed DC motor operated robotic hand. The gestures include pointing, grasping and stretching of the fingers. This project was intended to help amputated patients by studying data from healthy people.