Hand Gesture Recognition via sEMG signals with CNNs (Electrical and Computer Engineering - MSc Thesis)

The source code for the real-time hand gesture recognition algorithm based on Temporal Muscle Activation maps of multi-channel surface electromyography (sEMG) signals (ICASSP 2021)

Accompaniment code for 'Hilbert sEMG data scanning for hand gesture recognition based on Deep Learning' published in NCAA.

Source code for multiple parameter modelling of synthetic electromyography data.

Computationally-free personalization at test time for sEMG gesture classification. Fast (gpu/cpu) ninapro API.

Python algorithm to assess muscle activation patterns during cyclical movements

Auto-learning search framework based on a weighted double Q-learning algorithm:"Integrated block-wise neural network with auto-learning search framework for finger gesture recognition using sEMG signals"

Biomedical signal (EEG/sEMG/ECG) completion/imputation using diffusion model. "A robust denoising diffusion framework for completing missing regions of multiple biomedical signals"

Bachelor Thesis work developed in 2025 at University of Bologna. See Readme for more information on the project.

✋ Detect and count hand gestures in real-time using MediaPipe and OpenCV, enabling intuitive human-computer interaction applications.