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

Table of contents

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.