Determination of psychotic behaviour using a network of chemical oscillators

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Authors
Bose, Ashmita
Gorecki, Jerzy
Date
2020
Journal Title
Journal ISSN
Volume Title
Publisher
International Frequency Sensor Association (IFSA) Publishing, S. L.
License
Creative Commons License
Creative Commons Attribution 3.0 Poland License
Abstract
Schizophrenia is the most common form of psychotic behaviour where patients experiences hallucination, dillusion or chaotic speech. Schizophrenia is difficult to detect and easily go undetected for years. Here we propose the idea of detecting schizophrenia by a network of interacting chemical oscillators. We optimized a classifier based on six interacting oscillator using genetic algorithm and obtained 82% accuracy of schizophrenia detection on a selected training dataset.
Description
Keywords
schizophrenia    EEG signal    chemical computing    oscillatory network    oregonator model    genetic optimization
Citation
Advances in Signal Processing and Artificial Intelligence: Proceedings of the 2nd International Conference on Advances in Signal Processing and Artificial Intelligence 18 - 20 November 2020 Berlin, Germany, Edited by Sergey Y. Yurish, pages 67-71
URI
https://depot.ceon.pl/handle/123456789/21157
Belongs to collection
Publikacje konferencyjne ICHF PAN / IPC PAC Conference Papers