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The electroencephalogram (EEG) records the brain's electrical activity acquired from invasive or noninvasive methods, chosen according to its aims and technical specificities. The EEG signal has been used for several purposes, such as the development of brain-machine interfaces, analysis, and treatment of neurological disorders (Alzheimer's, Parkinson's, and Epilepsy), sleep disorders, and wakefulness. It has been an important data source for the diagnosis of several diseases. This paper presents a wavelet-based dynamic artificial neural network (D-ANN) for brain wave recognition in the delta, theta, alpha, and beta bands with an accuracy of 98.3%. These EEG frequency bands are related to the usage of brain regions and, in general, may reveal either the state of the body or mind, such as when performing cognitive tasks, spelling and writing tasks, sports practice tasks, resting state, and even abnormal behavior. These wave recognition, followed by qualitative analysis, has great applicability in neurological disease diagnosis, which is one of its aims.

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Artificial Neural Network-Based Method for EEG Frequency Patterns Recognition

  • 会议论文

  • 发表日期：

    2025年

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  • Gilson J. Alves,
  • Diogo R. R. Freitas,
  • Ana V. M. Inocêncio,
  • J. V. S. Alves,
  • Renato Evangelista de Araujo,
  • Marco A. Benedetti Rodrigues

摘要

The electroencephalogram (EEG) records the brain's electrical activity acquired from invasive or noninvasive methods, chosen according to its aims and technical specificities. The EEG signal has been used for several purposes, such as the development of brain-machine interfaces, analysis, and treatment of neurological disorders (Alzheimer's, Parkinson's, and Epilepsy), sleep disorders, and wakefulness. It has been an important data source for the diagnosis of several diseases. This paper presents a wavelet-based dynamic artificial neural network (D-ANN) for brain wave recognition in the delta, theta, alpha, and beta bands with an accuracy of 98.3%. These EEG frequency bands are related to the usage of brain regions and, in general, may reveal either the state of the body or mind, such as when performing cognitive tasks, spelling and writing tasks, sports practice tasks, resting state, and even abnormal behavior. These wave recognition, followed by qualitative analysis, has great applicability in neurological disease diagnosis, which is one of its aims.