XAI-Driven sEMG Feature Analysis for Hand Gestures

Naveen Gehlot, Suryansh Malik, Ashutosh Jena, Ankit Vijayvargiya, Rajesh Kumar

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

Surface electromyography (sEMG) signals play a vital role in hand gesture recognition for identifying various hand movements. Due to its non-invasive nature and real-Time muscle activation detection capabilities, sEMG is widely employed in hand gesture identification. The utilization of Machine Learning (ML) for real-Time recognition of sEMG-based hand gestures is an emerging and evolving field. Along with this, the ML classifiers are also known as 'black boxes' since they cannot provide discernible insights into how decisions are produced and what factors impact them. Explainable Artificial Intelligence (XAI) is employed to emphasize the importance of specific features in machine learning models. In this study, employed data related to six hand gestures to assess the performance of five different machine learning models. Among these classifiers, the Extra Tree model demonstrated the highest accuracy, achieving an impressive 85.22%. Furthermore, the XAI-LIME model has been employed to investigate these models' feature relevance for all six hand gestures under examination.

Original languageEnglish
Title of host publication2024 3rd International Conference on Power, Control and Computing Technologies, ICPC2T 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages19-24
Number of pages6
ISBN (Electronic)9798350349207
DOIs
Publication statusPublished - 2024
Externally publishedYes
Event3rd International Conference on Power, Control and Computing Technologies, ICPC2T 2024 - Raipur, India
Duration: 18 Jan 202420 Jan 2024

Publication series

Name2024 3rd International Conference on Power, Control and Computing Technologies, ICPC2T 2024

Conference

Conference3rd International Conference on Power, Control and Computing Technologies, ICPC2T 2024
Country/TerritoryIndia
CityRaipur
Period18/01/2420/01/24

Keywords

  • Electromyography
  • Hand Gesture
  • LIME
  • Machine Learning
  • XAI

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering
  • Safety, Risk, Reliability and Quality
  • Control and Optimization

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