Development of an EMG based classification model that performs Hand Gesture Recognition optimally.

Table of contents

• General Info
• Technologies
• Performance Evaluation
• Setup

General Info

• This project is an Implementation of an online feature based MLP Classification of Hand Gesture’s EMG Signals
• Selected Features of EMG Signal:

1. Mean Frequency
2. Peak-to-Peak Frequency
3. Variance
4. Standard Deviation

• Multilayer perceptron is trained by using Back Porpagation Algorithm

Technologies

Project is created with:

• Python version: 3.6.7
• Anaconda
• Spyder IDE
• librairies used in this research
  • numpy
  • pandas
  • scikitlearn
  • matplotlib

Performance Evaluation

• Two metrics use to evaluate the model
• Confusion matrix
• ROC Curve

Setup

To run this project, install it locally using python ver 3.6.7, Anaconda.