Electromyography Signal Based Hand Gesture Classification System Using Hilbert Huang Transform and Deep Neural Networks-Reference-Cited by-同舟云学术

Electromyography Signal Based Hand Gesture Classification System Using Hilbert Huang Transform and Deep Neural Networks

Published:2023-03-23 Issue: Volume: Page:
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Author:

S Mary Vasanthi¹,T Jayasree²,A HAITER LENIN³^ORCID

Affiliation:

1. St Xavier's Catholic College of Engineering

2. Government College of Engineering Tirunelveli

3. Wollo University

Abstract

Abstract In this paper, classification of hand gestures for the smart control of prosthetic hands is proposed. The surface Electromyography (sEMG) signals are used for classifying the hand gestures. The important attributes of the signal are extracted by finding Hilbert Huang Transform (HHT). These features are given as input to the Deep Neural Network (DNN) classifier for further classification. The experimental results show that high classification accuracy can be achieved for the proposed method compared to the other techniques.

Publisher

Research Square Platform LLC

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