technical-note

Classification of EEG signals using a novel genetic programming approach

Authors:

Arpit Bhardwaj,

M. Vishaal Varma, and

M. Ramesh KrishnaAuthors Info & Claims

GECCO Comp '14: Proceedings of the Companion Publication of the 2014 Annual Conference on Genetic and Evolutionary Computation

July 2014

Pages 1297 - 1304

https://doi.org/10.1145/2598394.2609851

Published: 12 July 2014 Publication History

Abstract

In this paper, we present a new method for classification of electroencephalogram (EEG) signals using Genetic Programming (GP). The Empirical Mode Decomposition (EMD) is used to extract the features of EEG signals which served as an input for the GP. In this paper, new constructive crossover and mutation operations are also produced to improve GP. In these constructive crossover and mutation operators hill climbing search is integrated to remove the destructive nature of these operators. To improve GP, we apply constructive crossover on all the individuals which remain after reproduction. A new concept of selecting the global prime off-springs of the generation is also proposed. The constructive mutation approach is applied to poor individuals who are left after selecting globally prime off-springs. Improvement of the method is measured against classification accuracy, training time and the number of generations for EEG signal classification. As we show in the results section, the classification accuracy can be estimated to be 98.69% on the test cases, which is better than classification accuracy of Liang and coworkers method which was published in 2010.

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Cited By

Bhardwaj HTomar PSakalle ABhardwaj AAsthana RVidyarthi A(2023)EEG based personality prediction using genetic programmingAsian Journal of Control10.1002/asjc.301925:5(3330-3342)Online publication date: 4-Sep-2023
https://dl.acm.org/doi/10.1002/asjc.3019
Singh TBhadwaj HVerma LNavadia NSingh DSakalle ABhardwaj A(2022)Applications of AI in AgricultureChallenges and Opportunities for Deep Learning Applications in Industry 4.010.2174/9789815036060122010011(181-203)Online publication date: 3-Oct-2022
https://doi.org/10.2174/9789815036060122010011
Singh TSingh DBedi S(2021)Monitoring and Detecting Plant Diseases Using Cloud-Based Internet of ThingsIntegration and Implementation of the Internet of Things Through Cloud Computing10.4018/978-1-7998-6981-8.ch011(217-235)Online publication date: 2021
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Index Terms

Classification of EEG signals using a novel genetic programming approach
1. Computing methodologies
  1. Artificial intelligence
    1. Search methodologies
      1. Heuristic function construction

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cover image ACM Conferences

GECCO Comp '14: Proceedings of the Companion Publication of the 2014 Annual Conference on Genetic and Evolutionary Computation

July 2014

1524 pages

ISBN:9781450328814

DOI:10.1145/2598394

Editor-in-chief:
Christian Igel
Ruhr University of Bochum, University of Copenhagen
,
General Chair:
Dirk V. Arnold
Dalhousie University

Copyright © 2014 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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SIGEVO: ACM Special Interest Group on Genetic and Evolutionary Computation

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 12 July 2014

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GECCO '14

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SIGEVO

GECCO '14: Genetic and Evolutionary Computation Conference

July 12 - 16, 2014

BC, Vancouver, Canada

Acceptance Rates

GECCO Comp '14 Paper Acceptance Rate 180 of 544 submissions, 33%;

Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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Cited By

Bhardwaj HTomar PSakalle ABhardwaj AAsthana RVidyarthi A(2023)EEG based personality prediction using genetic programmingAsian Journal of Control10.1002/asjc.301925:5(3330-3342)Online publication date: 4-Sep-2023
https://dl.acm.org/doi/10.1002/asjc.3019
Singh TBhadwaj HVerma LNavadia NSingh DSakalle ABhardwaj A(2022)Applications of AI in AgricultureChallenges and Opportunities for Deep Learning Applications in Industry 4.010.2174/9789815036060122010011(181-203)Online publication date: 3-Oct-2022
https://doi.org/10.2174/9789815036060122010011
Singh TSingh DBedi S(2021)Monitoring and Detecting Plant Diseases Using Cloud-Based Internet of ThingsIntegration and Implementation of the Internet of Things Through Cloud Computing10.4018/978-1-7998-6981-8.ch011(217-235)Online publication date: 2021
https://doi.org/10.4018/978-1-7998-6981-8.ch011
Bhardwaj HTomar PSakalle ASingh TAcharya DBhardwaj A(2021)Future Aspects and Research Perspectives of the Internet of ThingsIntegration and Implementation of the Internet of Things Through Cloud Computing10.4018/978-1-7998-6981-8.ch001(1-18)Online publication date: 2021
https://doi.org/10.4018/978-1-7998-6981-8.ch001
Bhardwaj HTomar PSakalle AIbrahim W(2021)EEG-Based Personality Prediction Using Fast Fourier Transform and DeepLSTM ModelComputational Intelligence and Neuroscience10.1155/2021/65248582021Online publication date: 1-Jan-2021
https://dl.acm.org/doi/10.1155/2021/6524858
Bhardwaj HTomar PSakalle AAcharya DBhardwaj A(2021)Personality Prediction Using EEG Signals and Machine Learning AlgorithmsSoft Computing for Problem Solving10.1007/978-981-16-2712-5_10(109-114)Online publication date: 14-Oct-2021
https://doi.org/10.1007/978-981-16-2712-5_10
Acharya DLende MLathia KShirgurkar SKumar NMadrecha SBhardwaj A(2021)Comparative Analysis of Feature Extraction Technique on EEG-Based DatasetSoft Computing for Problem Solving10.1007/978-981-16-2709-5_31(405-416)Online publication date: 14-Oct-2021
https://doi.org/10.1007/978-981-16-2709-5_31
Acharya DTiwari MBhulakshmi Devi BShaikh SNatarajan KMaria Babu ABhardwaj A(2021)Feature Extraction for Classification Methods of EEG SignalsSoft Computing for Problem Solving10.1007/978-981-16-2709-5_29(381-392)Online publication date: 14-Oct-2021
https://doi.org/10.1007/978-981-16-2709-5_29
Acharya DJain RPanigrahi SSahni RJain SDeshmukh SBhardwaj A(2021)Multi-class Emotion Classification Using EEG SignalsAdvanced Computing10.1007/978-981-16-0401-0_38(474-491)Online publication date: 11-Feb-2021
https://doi.org/10.1007/978-981-16-0401-0_38
Bhardwaj HTomar PSakalle ABhardwaj A(2021)Classification of Extraversion and Introversion Personality Trait Using Electroencephalogram SignalsArtificial Intelligence and Sustainable Computing for Smart City10.1007/978-3-030-82322-1_3(31-39)Online publication date: 29-Jul-2021
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