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Short Time Frequency Analysis of Theta Activity for the Diagnosis of Bruxism on EEG Sleep Record

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Advanced Computational Intelligence Techniques for Virtual Reality in Healthcare

Part of the book series: Studies in Computational Intelligence ((SCI,volume 875))

Abstract

Sleep is the important part of the living organism. If the normal humans do not sleep properly so its generate many diseases. Bruxism is a neurological or sleep syndrome. Its individuals involuntarily grind the teeth. Bruxism covered in 8–31% of the whole sleep disorders like Insomnia, Narcolepsy etc. The present research focused on three steps such as data selection, filtration, and normalized value of theta activity. Additionally, the three sleep stages of non rapid eye movement such as S0, S1, S2 and rapid eye movement. In addition to parietal occipital (P4-O2) Electroencephalogram (EEG), channels are used in the present work. The total number of eighteen subjects such as bruxism and healthy human studied to this work. The average value of the normal human’s theta activity is higher than bruxism in all sleep stages such as S0, S1, S2 and rapid eye movement. Moreover, the proposed research is in accurate than other traditional system.

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Acknowledgements

The authors would like to thanks Dr. Faez Iqbal Khan, Prof. Naseem, Prof. Siddiqui, and Prof. Quddus for useful discussion. It’s also acknowledge BMI-EP, Laboratory, UESTC, Chengdu, Sichuan, China for providing biomedical and computational equipment. The National Natural Science Foundation of China under grant 61771100 supported this work.

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Authors and Affiliations

  1. Biomedical Imaging and Electrophysiology Laboratory, University of Electronic Science and Technology of China, Chengdu, Sichuan, China

    Md Belal Bin Heyat & Dakun Lai

  2. School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan, China

    Faijan Akhtar

  3. Lucknow, UP, India

    Mohd Ammar Bin Hayat & Shajan Azad

  4. Hayat Institute of Nursing, Lucknow, Uttar Pradesh, India

    Shajan Azad

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  1. Md Belal Bin Heyat
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  2. Dakun Lai
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Correspondence to Dakun Lai .

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Editors and Affiliations

  1. Department of Computer Science and Engineering, Maharaja Agrasen Institute of Technology, Guru Gobind Singh Indraprastha University, New Delhi, India

    Deepak Gupta

  2. Faculty of Computers and Information, Cairo University, Cairo, Egypt

    Aboul Ella Hassanien

  3. Department of Computer Science and Engineering, Maharaja Agrasen Institute of Technology, Guru Gobind Singh Indraprastha University, New Delhi, India

    Ashish Khanna

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Heyat, M.B.B., Lai, D., Akhtar, F., Hayat, M.A.B., Azad, S. (2020). Short Time Frequency Analysis of Theta Activity for the Diagnosis of Bruxism on EEG Sleep Record. In: Gupta, D., Hassanien, A., Khanna, A. (eds) Advanced Computational Intelligence Techniques for Virtual Reality in Healthcare. Studies in Computational Intelligence, vol 875. Springer, Cham. https://doi.org/10.1007/978-3-030-35252-3_4

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