https://github.com/aqc-github/myo-ml

Repository for the machine learning and AI models developed during my final master thesis on "Characterization of sEMG signals and classification-powered prostheses control."
https://github.com/aqc-github/myo-ml

Last synced: over 1 year ago
JSON representation

Repository for the machine learning and AI models developed during my final master thesis on "Characterization of sEMG signals and classification-powered prostheses control."

• Host: GitHub
• URL: https://github.com/aqc-github/myo-ml
• Owner: aqc-github
• License: mit
• Created: 2023-10-06T13:13:59.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2024-09-04T01:38:40.000Z (almost 2 years ago)
• Last Synced: 2024-09-09T21:39:46.498Z (almost 2 years ago)
• Language: Python
• Size: 3.64 MB
• Stars: 2
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

          
# Characterization of sEMG signals and classification-powered prostheses control.

### by: A. Quintana Criado

## 4th September 2024

The project is now over into another repo. I had to fully restart everything back in June 24. See: https://github.com/Quintanaaalberto/GraspNet-MEng

## 19th February 2024. 

The project has been restarted completely. The new goal of the project is to train a Deep Learning model to classify the sEMG signals in the Dataset called Ninapro DB10 from the Harvard database.  -> https://ninapro.hevs.ch/instructions/DB10.html  There are two approaches in mind right now:

* 1st approach: CNN model to classify 12 channels of sEMG as a timeseries (signal)

* 2nd approach: CNN model to classify the sEMG as images