research-article

Intersected EMG Heatmaps and Deep Learning Based Gesture Recognition

Authors:

Gaetano Di Caterina,

Lykourgos Petropoulakis,

John SoraghanAuthors Info & Claims

ICMLC '20: Proceedings of the 2020 12th International Conference on Machine Learning and Computing

Pages 73 - 78

https://doi.org/10.1145/3383972.3383982

Published: 26 May 2020 Publication History

Abstract

Hand gesture recognition in myoelectric based prosthetic devices is a key challenge to offering effective solutions to hand/lower arm amputees. A novel hand gesture recognition methodology that employs the difference of EMG energy heatmaps as the input of a specific designed deep learning neural network is presented. Experimental results using data from real amputees indicate that the proposed design achieves 94.31% as average accuracy with best accuracy rate of 98.96%. A comparison of experimental results between the proposed novel hand gesture recognition methodology and other similar approaches indicates the superior effectiveness of the new design.

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Cited By

Wang FAo XWu MKawata SShe J(2024)Explainable Deep Learning for sEMG-Based Similar Gesture Recognition: A Shapley-Value-Based SolutionInformation Sciences10.1016/j.ins.2024.120667(120667)Online publication date: May-2024
https://doi.org/10.1016/j.ins.2024.120667
Ni SAl-qaness MHawbani AAl-Alimi DAbd Elaziz MEwees A(2024)A survey on hand gesture recognition based on surface electromyography: Fundamentals, methods, applications, challenges and future trendsApplied Soft Computing10.1016/j.asoc.2024.112235166(112235)Online publication date: Nov-2024
https://doi.org/10.1016/j.asoc.2024.112235
Eddy EScheme EBateman S(2023)A Framework and Call to Action for the Future Development of EMG-Based Input in HCIProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3580962(1-23)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544548.3580962
Show More Cited By

Index Terms

Intersected EMG Heatmaps and Deep Learning Based Gesture Recognition
1. Computing methodologies
  1. Machine learning
    1. Machine learning approaches
      1. Neural networks

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ICMLC '20: Proceedings of the 2020 12th International Conference on Machine Learning and Computing

February 2020

607 pages

ISBN:9781450376426

DOI:10.1145/3383972

Copyright © 2020 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Shenzhen University: Shenzhen University

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 26 May 2020

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ICMLC 2020

ICMLC 2020: 2020 12th International Conference on Machine Learning and Computing

February 15 - 17, 2020

Shenzhen, China

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Cited By

Wang FAo XWu MKawata SShe J(2024)Explainable Deep Learning for sEMG-Based Similar Gesture Recognition: A Shapley-Value-Based SolutionInformation Sciences10.1016/j.ins.2024.120667(120667)Online publication date: May-2024
https://doi.org/10.1016/j.ins.2024.120667
Ni SAl-qaness MHawbani AAl-Alimi DAbd Elaziz MEwees A(2024)A survey on hand gesture recognition based on surface electromyography: Fundamentals, methods, applications, challenges and future trendsApplied Soft Computing10.1016/j.asoc.2024.112235166(112235)Online publication date: Nov-2024
https://doi.org/10.1016/j.asoc.2024.112235
Eddy EScheme EBateman S(2023)A Framework and Call to Action for the Future Development of EMG-Based Input in HCIProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3580962(1-23)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544548.3580962
Griffith THubbard JBalas MGriffith THubbard JBalas M(2023)Modal Analysis of Brain Wave DynamicsA Modal Approach to the Space-Time Dynamics of Cognitive Biomarkers10.1007/978-3-031-23529-0_4(65-80)Online publication date: 24-Feb-2023
https://doi.org/10.1007/978-3-031-23529-0_4
Kumar DGanesh A(2022)A Critical Review on Hand Gesture Recognition using sEMG: Challenges, Application, Process and TechniquesJournal of Physics: Conference Series10.1088/1742-6596/2327/1/0120752327:1(012075)Online publication date: 1-Aug-2022
https://doi.org/10.1088/1742-6596/2327/1/012075
Ke WXing YDi Caterina GPetropoulakis LSoraghan J(2020)Deep Convolutional Spiking Neural Network Based Hand Gesture Recognition2020 International Joint Conference on Neural Networks (IJCNN)10.1109/IJCNN48605.2020.9207040(1-7)Online publication date: Jul-2020
https://doi.org/10.1109/IJCNN48605.2020.9207040

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