Power Spectrum Characteristics of EEG Channels during Awake and REM Sleep Stages for Bruxism Patients
Authors: 
Chunwu Wang, Ajay K. Verma, Shubha Majumder, Xin Xiong, Chunling Liu, Bijay GuragainAuthors Info & Claims
Pages 114 - 118
Abstract
Sleep bruxism can lead to excessive strain on teeth and pain in the facial region and is a recognized sleep disorder adversely impacting people of all age group. People are typically unaware of sleep bruxism and unable to minimize the associated damage. Thus, identification of bruxism will be crucial in devising preventive strategies for excessive teeth damage. Electroencephalography (EEG) has been extensively studied to characterize bruxism, however, frequency and spatial modulations in EEG spectra related to sleep bruxism remains understudied. To address this limitation, we analyzed EEG frequency bands to compare the dynamics of EEG power spectrum from five common bipolar recordings of bruxism patients and Healthy control group during rapid eye movement (REM) sleep. Data from 2 bruxism patients (age: 28.5±3.89 years, mean±SE; 2 males) and 4 Healthy control group (age: 30.25±2.53 years, mean±SE; 3 females) were analyzed. Relative power spectral density (relative PSD) in delta (1-4 Hz), theta (4-8 Hz), alpha (8-13 Hz), and beta (13-30 Hz) bands in five EEG bipolar channels (F4C4, C4P4, Fp1F3, F3C3, and C4A1) were analyzed. The statistical comparison demonstrated that compared with the health controls, patients with bruxism showed a significant higher in relative PSD alpha by 135.44% in the awake stage of the F3C3 channel, and a significant higher relative PSD beta by 65.77% in the Fp1F3 channel during the REM sleep phase. In addition, the relative PSD theta significantly decreased during the REM sleep stage of the health control group, but increased significantly in patients with bruxism. The research findings emphasize the potential of 1) neural oscillation changes related to bruxism on different channels, and 2) single channel EEG in the development of sleep bruxism recognition systems.
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Index Terms
- Power Spectrum Characteristics of EEG Channels during Awake and REM Sleep Stages for Bruxism Patients
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October 2023
1394 pages
ISBN:9798400708138
DOI:10.1145/3644116
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Published: 05 April 2024
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ISAIMS 2023: 2023 4th International Symposium on Artificial Intelligence for Medicine Science
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