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Evaluating Ratio Indices Based on Electroencephalogram Brainwaves in Schizophrenia Detection

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Abstract

Purpose

Extensive research has been conducted by neurocognitive and psychological scientists to diagnose mental and neurological diseases intelligently. Recently, researchers have shown interest in Electroencephalogram (EEG) analysis, a non-invasive method of recording the brain’s electrical activity from the scalp surface. EEG signals contain different frequency bands, each indicating specific brain activities. Although the relative powers of single EEG waves are not all-inclusive indicators to consistently imitate mental involvement, ratio indices should be considered. These indices calculate the ratio of powers (summations) with more than a single frequency band.

Methods

This study quantifies the EEG signals of healthy control and schizophrenic groups using thirty-seven ratio indices based on EEG brainwaves. These indicators are examined for the first time in schizophrenia. The study evaluates which index is more suitable and efficient for solving a classification problem.

Results

The results show the potential of (delta + theta)/alpha in the schizophrenia classification with an average accuracy of 97.92%. Additionally, the study investigates the effectiveness of different EEG electrodes in the problem of schizophrenia diagnosis while utilizing the above indicators. T5, the left posterior temporal region, yields a maximum average accuracy of 92.92%.

Conclusion

In conclusion, the fusion of EEG frequency ratio indices and machine learning algorithms provides a potential avenue for improving the detection and diagnosis of schizophrenia.

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Data Availability

The RepOD dataset [19, 20] analyzed in this experiment is freely available at public domain.

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Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Author information

Authors and Affiliations

  1. Department of Biomedical Engineering, Faculty of Electrical Engineering, Sahand University of Technology, Tabriz, Iran

    Atefeh Goshvarpour

  2. Department of Biomedical Engineering, Imam Reza International University, Mashhad, Razavi Khorasan, Iran

    Ateke Goshvarpour

  3. Health Technology Research Center, Imam Reza International University, Mashhad, Razavi Khorasan, Iran

    Ateke Goshvarpour

Authors
  1. Atefeh Goshvarpour
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  2. Ateke Goshvarpour
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Both authors were equally involved in the study. The main person responsible for writing the manuscript was Ateke Goshvarpour.

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Correspondence to Ateke Goshvarpour.

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This article examined EEG signals of the RepOD [19, 20], freely available in the public domain. This article contains no studies with human participants performed by any authors.

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Goshvarpour, A., Goshvarpour, A. Evaluating Ratio Indices Based on Electroencephalogram Brainwaves in Schizophrenia Detection. J. Med. Biol. Eng. 44, 127–143 (2024). https://doi.org/10.1007/s40846-024-00851-1

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  • DOI: https://doi.org/10.1007/s40846-024-00851-1

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