Nature and Science of Sleep (Apr 2021)

Spectral Power Analysis of Sleep Electroencephalography in Subjects with Different Severities of Obstructive Sleep Apnea and Healthy Controls

  • Kang JM,
  • Cho SE,
  • Na KS,
  • Kang SG

Journal volume & issue
Vol. Volume 13
pp. 477 – 486

Abstract

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Jae Myeong Kang,1,2,* Seo-Eun Cho,2,* Kyoung-Sae Na,2 Seung-Gul Kang1,2 1Sleep Medicine Center, Gil Medical Center, Gachon University College of Medicine, Incheon, Republic of Korea; 2Department of Psychiatry, Gil Medical Center, Gachon University College of Medicine, Incheon, Republic of Korea*These authors contributed equally to this workCorrespondence: Seung-Gul KangDepartment of Psychiatry, Gil Medical Center, Gachon University, College of Medicine, 21, Namdong-daero 774 Beon-gil, Namdong-gu, Incheon, 21565, Republic of KoreaTel +82 32-458-2818Email [email protected]: Previous spectral analysis studies on obstructive sleep apnea (OSA) involved small samples, and the results were inconsistent. We performed a spectral analysis of sleep EEG based on different severities of OSA using the Sleep Heart Health Study data. This study aimed to determine the difference in EEG spectral power during sleep in the non-OSA group and with different severities of OSA in the general population.Patients and Methods: The participants (n = 5,804) underwent polysomnography, and they were classified into non-OSA, mild OSA, moderate OSA, and severe OSA groups. The fast Fourier transformation was used to compute the EEG power spectrum for total sleep duration within contiguous 30-second epochs of sleep. The EEG spectral powers of the groups were compared using 4,493 participants after adjusting potential confounding factors that could affect sleep EEG.Results: The power spectra differed significantly among the groups for all frequency bands (p corr < 0.001). We found that the quantitative EEG spectral powers in the beta and sigma bands of total sleep differed (p corr < 0.001) among the participants in the non-OSA group and with different severities of OSA, controlling for covariates. The beta power was higher and the sigma power was lower in the OSA groups than in the non-OSA group. The beta power decreased in the order of severe OSA, moderate OSA, mild OSA, and non-OSA.Conclusion: This study suggests that there are differences between the microstructures of PSG-derived sleep EEG of non-OSA participants and those with different severities of OSA.Keywords: sleep EEG, spectral power, polysomnography, OSA, beta power, sigma power

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