王瑶, 杨天顺, 纪思宇, 王小红, 王慧泉, 王金海, 赵晓赟. 基于脑电小波分解的呼吸暂停自动检测方法[J]. 中国生物医学工程学报, 2022, 41(3): 370-374.
Wang Yao, Yang Tianshun, Ji Siyu, Wang Xiaohong, Wang Huiquan, Wang Jinhai, Zhao Xiaoyun. An Automated Apnea Detection Method Based on Wavelet Decomposition of EEG Signals. Chinese Journal of Biomedical Engineering, 2022, 41(3): 370-374.
[1] Berry RB, Budhiraja R, Gottlieb DJ, et al. Rules for scoring respiratory events in sleep: update of the 2007 AASM manual for the scoring of sleep and associated events [J]. Journal of Clinical Sleep Medicine, 2012, 8(5): 597619. [2] Pan CK, Vail D, Bhattacharya J, et al. The effect of obstructive sleep apnea on absolute risk of central serous chorioretinopathy [J]. American Journal of Ophthalmology, 2020, 218: 148-155. [3] Kokkarinen J. Obstructive sleep apnea-hypopnea and incident stroke: the sleep heart health study [J]. American Journal of Respiratory and Critical Care Medicine, 2011, 183(7): 950-950. [4] Rolon RE, Gareis, IE, Larrateguy, LD, et al. Automatic scoring of apnea and hypopnea events using blood oxygen saturation signals [J]. Biomedical Signal Processing and Control, 2020, 62: 102062. [5] Marcus CL, Brooks LJ, Ward SD, et al. Diagnosis and management of childhood obstructive sleep apnea syndrome [J]. Pediatrics, 2012, 130(3): E714-E755. [6] Tripathy RK, Gajbhiye P, Acharya UR. Automated sleep apnea detection from cardio-pulmonary signal using bivariate fast and adaptive EMD coupled with cross time-frequency analysis [J]. Computers in Biology and Medicine, 2020, 120: 103769. [7] Tripathy RK, Acharya UR. Automated detection of sleep apnea using sparse residual entropy features with various dictionaries extracted from heart rate and EDR signals [J]. Computers in Biology and Medicine, 2019, 108: 20-30. [8] Wang Lei, Lin Youfang, Wang Jing. A RR interval based automated apnea detection approach using residual network [J]. Computer Methods and Programs in Biomedicine, 2019, 176: 93-104. [9] Janbakhshi P, Shamsollahi MB. Sleep apnea detection from single-lead ECG using features based on ECG-derived respiration (EDR) signals [J]. IRBM, 2018, 393(3): 206-218. [10] Choi SH, Yoon H, Kim HS, et al. Real-time apnea-hypopnea event detection during sleep by convolutional neural networks [J]. Computers in Biology and Medicine, 2018, 100: 123-131. [11] Bhattacharjee A, Saha S, Fattah, SA, et al. Sleep apnea detection based on rician modeling of feature variation in multiband EEG signal [J]. IEEE Journal of Biomedical and Health Informatics, 2019, 23(3): 1066-1074. [12] Shahnaz C, Minhaz AT, Ahamed ST. Sub-frame based apnea detection exploiting delta band power ratio extracted from EEG signals [C] // Proceedings of the 2016 IEEE Region 10 Conference (TENCON). New York: IEEE, 2016: 190-193. [13] Zhou Jing, Wu Xiaoming, Zeng Weijie. Automatic detection of sleep apnea based on EEG detrended fluctuation analysis and support vector machine [J]. Journal of Clinical Monitoring and Computing, 2015, 29(6): 767-772. [14] 颜世玉,刘 冲,赵海滨,等. 基于小波包分解的意识脑电特征提取 [J]. 仪 器 仪 表 学 报, 2012, 33(8): 1748-1752. [15] Liu Da, Niu Dongxiao, Wang Hui, et al. Short-term wind speed forecasting using wavelet transform and support vector machines optimized by genetic algorithm [J]. Renewable Energy, 2014, 62: 592-597. [16] 覃恒基, 刘官正. 基于自编码器和隐马尔可夫模型的睡眠呼吸暂停检测方法 [J]. 中国生物医学工程学报, 2020, 4: 422-431. [17] 余辉, 王硕, 李心蕊,等. 基于LSTM-CNN的睡眠呼吸暂停与低通气事件实时检测算法研究[J]. 中国生物医学工程学报, 2020,39(3): 303-310. [18] Guijarro-Berdinas B, Hernandez-Pereira E, Peteiro-Barral D. A mixture of experts for classifying sleep apneas [J]. Expert Syst Appl, 2012, 39(8): 7084-7092.
