Muscle Synergy Analysis of Hand Motion Using sEMG and Optical Tracking

Overview

This project presents a dual-modality framework for analyzing human hand motion using:

• Surface Electromyography (sEMG): to capture muscular activity.

• Optical Motion Tracking (Vicon): to capture kinematic data.

By combining these modalities, the system extracts muscle synergies through Sparse Non-Negative Matrix Factorization (sNMF) and compares them with 3D kinematic closure estimates.

Applications include rehabilitation, prosthetics, human–robot interaction, and gesture recognition.

Project Structure

code

The section containing all the scripts used for the analysis.

• analyze : folder containing scripts to visualize the main mathematical concepts used.
• dataset : folder containing the data aquired from the Vicon environment and from the BioGAP armband.
• ikpy : folder containing the ikpy library, directly downloaded into the project folder to manually make slight changes.
• results : folder containing result for all the different analysis carried out.
• tests : folder containing draft tests when we started the analysis of the dataset.
• utils : folder containing all the functions personally created for making the main scripts easier to understand.
• config.py : file that imports all the libraries used in the project.
• motion_tracking.py : file containing the final 3D model of the hand pipeline.
• sigma_flexion.py : file containing the final comparison of the closure level of the hand (more repetitions included).
• single_sigma_flexion.py : file containing the final comparison of the closure level of the hand.
• single_synergy_extraction.py : file containing the synergy extraction pipeline.
• synergy_extraction.py : file containing the synergy extraction pipeline (more repetitions included).

nodes

The folder containing ROS nodes for acquiring data for the Vicon environment. For the BioGAP armband refer to the github link contained in the 'info.txt' file of this folder.

setup_pics

The folder coontaining photos of the environment developed and material used.

Author

Riccardo Serraino

Contributor: Giuliano Livi

Bachelor’s Thesis in Automation Engineering University of Bologna, July 2025

Supervisors: Prof. Roberto Meattini, Alessandra Bernardini, Mattia Orlandi, Prof. Simone Benatti