Abstract：Sleep apnea syndrome (SAS) is a common sleep disorder. Traditionally, methods such as time-frequency analysis are used to study the abnormality of EEG signals, while ignoring the spatial location information and difference in characteristics. In this paper, the method of microstate analysis was used to analyze the EEG of five sleep stages (W, N1, N2, N3, REM) of healthy and SAS patients, and to explore the temporal and spatial differences in sleep EEG of SAS patients. The sleep EEG of 66 SAS patients and 10 healthy people was selected and the GFP of W-REM was calculated, and the GFP peak data were used for clustering. As a result, four microstates classes were obtained, the four microstate topographic maps were referred as right fronto-left posterior (A), left fronto-right posterior (B), fronto-occipital midline (C) and frontal midline (D), and the microstate parameters (occurrence frequency, average duration, coverage rate) were calculated. In addition, the static properties global explained variance (GEV), dynamic properties (entropy rate), transition probabilities, and symmetry of transition matrices of the microstate sequence were calculated. Finally, the Hurst index was used to evaluate the long-range correlation of microstate sequences. In the W-REM stage, there were significant differences in the frequency, average duration, coverage rate, GEV, conversion probability, entropy rate and Hurst index between the healthy people and SAS patients (P<0.05). The transfer matrix was symmetric (P>0.01). The Hurst index was greater than 0.5, with remote correlation. In conclusion, compared with the healthy people, SAS patients had altered microstate parameters and sequences in the W-REM stage.
熊馨, 杨鑫亮, 罗剑花, 易三莉, 贺建峰. 睡眠呼吸暂停综合症患者脑电微状态发生改变[J]. 中国生物医学工程学报, 2023, 42(5): 563-571.
Xiong Xin, Yang Xinliang, Luo Jianhua, Yi Sanli, He Jianfeng. Changes of EEG Microstate in Patients with Sleep Apnea Syndrome. Chinese Journal of Biomedical Engineering, 2023, 42(5): 563-571.
[1] 葛靖, 刘子龙. 基于CNN和LSTM的睡眠呼吸暂停检测算法[J]. 电子科技,2021,34(2):21-26. [2] Wolpert EA . A manual of standardized terminology, techniques and scoring system for sleep stages of human subjects[J]. Electroencephalography & Clinical Neurophysiology, 1969, 26(2):644-644. [3] Huang W, Guo B, Shen Y, et al. Sleep staging algorithm based on multichannel data adding and multifeature screening[J]. Computer Methods and Programs in Biomedicine, 2020, 187: 105253. [4] Hassan AR, Subasi A. A decision support system for automated identification of sleep stages from single-channel EEG signals[J]. Knowledge-Based Systems, 2017, 128:115-124. [5] 唐其彪. 基于脑电信号的自动睡眠分期研究[D]. 广州: 广东工业大学, 2016. [6] Zhu T, Luo W, Yu F. Convolution-and attention-based neural network for automated sleep stage classification[J]. International Journal of Environmental Research and Public Health, 2020, 17(11): 4152. [7] Pascual-Marqui RD, Michel CM, Lehmann D. Segmentation of brain electrical activity into microstates: model estimation and validation[J]. IEEE Transactions on Biomedical Engineering, 1995, 42(7): 658-665. [8] Milz P,Faber P,Lehmann D, et al. The functional significance of EEG microstates—Associations with modalities of thinking[J]. NeuroImage,2016,125:643-656. [9] Khanna A, Pascual-Leone A, Michel CM, et al. Microstates in resting-state EEG: current status and future directions[J]. Neuroscience and Biobehavioral Reviews, 2015 ,49: 105-113. [10] Stevens A , Kircher T . Cognitive decline unlike normal aging is associated with alterations of EEG temporo-spatial characteristics[J]. European Archives of Psychiatry & Clinical Neuroscience, 1998, 248(5):259-266. [11] Lehmann D, Faber PL, Galderisi S, et al. EEG microstate duration and syntax in acute, medication-naive, first-episode schizophrenia: a multi-center study[J]. Psychiatry Research: Neuroimaging, 2005, 138(2): 141-156. [12] Piorecka V, Piorecky M, Strobl J, et al. EEG microstates analysis in patients with epilepsy[J]. Lekar a Technika, 2018, 48(3):96-102. [13] Brodbeck V, Kuhn A, von Wegner F, et al. EEG microstates of wakefulness and NREM sleep[J]. Neuroimage, 2012, 62(3): 2129-2139. [14] Kuhn A, Brodbeck V, Tagliazucchi E, et al. Narcoleptic patients show fragmented EEG-microstructure during early NREM sleep[J]. Brain Topography, 2015 ,28(4): 619-635. [15] Britz J, Van De Ville D, Michel CM. Bold correlates of EEG topography reveal rapid resting-state network dynamics[J]. Neuroimage, 2010, 52(4): 1162-1170. [16] 张克旭, 杜昌旺, 赵浩淇, 等. 针对局灶性癫痫患者的脑电微状态分析[J]. 西安交通大学学报, 2020, 54(9): 157-163. [17] Zhang Kexu, Shi Wen, Wang Chang, at al. Reliability of EEG microstate analysis at different electrode densities during propofol-induced transitions of brain states[J]. Neuroimage, 2021, 231:117861. [18] Von Wegner F, Knaut P, Laufs H. EEG microstate sequences from different clustering algorithms are information-theoretically invariant[J]. Frontiers in Computational Neuroscience,2018,12:70. [19] Von Wegner F, Tagliazucchi E, Laufs H. Information-theoretical analysis of resting state EEG microstate sequences-non-markovianity, non-stationarity and periodicities[J]. Neuroimage, 2017, 158: 99-111. [20] Khalighi S, Sousa T, Santos JM, et al. Isruc-sleep: a comprehensive public dataset for sleep researchers[J]. Computer Methods and Programs in Biomedicine, 2016, 124: 180-192. [21] Lehmann D, Ozaki H, Pal I. EEG alpha map series: brain micro-states by space-oriented adaptive segentation[J]. Electroencephalography and Clinical Neurophysiology, 1987, 67(3): 271-288. [22] Lloyd S. Least squares quantization in PCM[J]. IEEE Transactions on Information Theory, 1982, 28(2): 129-137. [23] Levin DA, Peres Y, Wilmer EL .Markov chains and mixing times[M]. New York: American Mathematical Society, 2006. [24] Kullback S, Kupperman M, Ku H. Tests for contingency tables and marltov chains[J]. Technometrics, 1962, 4(4): 573-608. [25] Veitch D, Abry P. A wavelet based joint estimator of the parameters of long-range dependence[J]. IEEE Transactions on Information Theory, 1999, 45(3): 878-897. [26] Van de Ville D, Britz J, Michel CM, et al. EEG microstate sequences in healthy humans at rest reveal scale-free dynamics[J]. Proceedings of the National Academy of Sciences, 2010, 107(42): 18179-18184. [27] 荣红佳, 盛虎, 闫秋婷. 基于改进R/S估计算法的网络流量长相关性分析[J]. 大连交通大学学报, 2021, 42(2): 114-119. [28] Bréchet L, Brunet D, Perogamvros L, et al. EEG microstates of dreams[J]. Scientific Reports, 2020, 10(1): 1-9. [29] Simor P, van der Wijk G, Nobili L, et al. The microstructure of REM sleep: Why phasic and tonic?[J]. Sleep Medicine Reviews, 2020, 52:101305. [30] Peigneux P, Laureys S, Fuchs S, et al. Generation of rapid eye movements during paradoxical sleep in humans[J]. Neuroimage, 2001, 14(3): 701-708. [31] Murphy M, Stickgold R, Öngür D. Electroencephalogram microstate abnormalities in early-course psychosis[J]. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 2020, 5(1): 35-44. [32] 吉维忠. 睡眠呼吸暂停综合症患者认知功能障碍临床研究[D]. 昆明:昆明医学院, 2005. [33] Ke Ming, Li Jianpan, Wang Lubin. Alteration in resting-state EEG microstates following 24 hours of total sleep deprivation in healthy young male subjects[J]. Frontiers in Human Neuroscience, 2021, 15: 175.
