[1] Wu H, Stone W S, Hsi X, et al. Effects of different sleep restriction protocols on sleep architecture and daytime vigilance in healthy men[J]. Physiological Research, 2010, 59(5):821-829. [2] Cafer A, Ahmet A, Feng L, et al. Sleep apnea classification based on respiration signals by using ensemble methods[J]. Bio-Medical Materials and Engineering, 2015, 26(1):1703-1710. [3] Haidar R, McCloskey S, Koprinska I, et al. Convolutional neural networks on multiple respiratory channels to detect hypopnea and obstructive apnea events[C]//International Joint Conference on Neural Networks.[S.l.]:IEEE Press, 2018:1-7. [4] Kagawa M, Tojima H, Matsui T. Non-contact diagnostic system for sleep apnea-hypopnea syndrome based on amplitude and phase analysis of thoracic and abdominal Doppler radars[J]. Medical & Biological Engineering & Computing, 2016, 54(5):789-798. [5] Chen Y C, Hsiao T C. Instantaneous phase difference analysis between thoracic and abdominal movement signals based on complementary ensemble empirical mode decomposition[J]. BioMedical Engineering OnLine, 2016, 15(1):1-21. [6] Maali Y, Al-Jumaily A. Automated detecting sleep apnea syndrome:a novel system based on genetic SVM[C]//International Conference on Hybrid Intelligent Systems. Melacca:IEEE Press, 2011:590-594. [7] Koley B L, Dey D. Automated detection of apnea and hypopnea events[C]//Third International Conference on Emerging Applications of Information Technology. Kolkata:IEEE Press, 2013:85-88. [8] Gutiérrez-Tobal G, Alvarez D, Del Campo F, et al. Utility of adaBoost to detect sleep apnea-hypopnea syndrome from single-channel airflow[J]. IEEE Transactions on Biomedical Engineering, 2016, 63(3):636-647. [9] Bianchi M T, Lipoma T, Darling C, et al. Automated sleep apnea quantification based on respiratory movement[J]. International Journal of Medical Sciences, 2014, 11(8):796-802. [10] Koley B L, Dey D. Real-time adaptive apnea and hypopnea event detection methodology for portable sleep apnea monitoring devices[J]. IEEE Transactions on Biomedical Engineering, 2013, 60(12):3354-3363. [11] Barroso-García V, Gutiérrez-Tobal G, Leila K G, et al. Irregularity and variability analysis of airflow recordings to facilitate the diagnosis of paediatric sleep apnoea-hypopnoea syndrome[J]. Entropy, 2017, 19(9):447-463. [12] Minu P, Amithab M. SAHS detection based on ANFIS using single channel airflow signal[J]. International Journal of Innovative Research in Science, Engineering and Technology, 2016, 5(7):13053-13061. |