A hierarchical classification method for automatic sleep scoring using multiscale entropy features and proportion information of sleep architecture

Holland, 1974, Polysomnography: a response to a need for improved communication, 121 Wolpert, 1969, A manual of standardized terminology, techniques and scoring system for sleep stages of human subjects, Arch Gen Psychiatry, 20, 246, 10.1001/archpsyc.1969.01740140118016 Silber, 2007, The visual scoring of sleep in adults, J Clin Sleep Med, 3, 121, 10.5664/jcsm.26814 Stanus, 1987, Automated sleep scoring: a comparative reliability study of two algorithms, Electroencephalogr Clin Neurophysiol, 66, 448, 10.1016/0013-4694(87)90214-8 Norman, 2000, Interobserver agreement among sleep scorers from different centers in a large dataset, Sleep, 23, 901, 10.1093/sleep/23.7.1e Agarwal, 2001, Computer-assisted sleep staging, IEEE Trans Biomed Eng, 48, 1412, 10.1109/10.966600 Tagluk, 2010, Estimation of sleep stages by an artificial neural network employing EEG, EMG and EOG, J Med Syst, 34, 717, 10.1007/s10916-009-9286-5 Khalighi, 2013, Automatic sleep staging: a computer assisted approach for optimal combination of features and polysomnographic channels, Expert Syst Appl, 40, 7046, 10.1016/j.eswa.2013.06.023 Özşen, 2013, Classification of sleep stages using class-dependent sequential feature selection and artificial neural network, Neural Comput Appl, 23, 1239, 10.1007/s00521-012-1065-4 Fraiwan, 2012, Automated sleep stage identification system based on time–frequency analysis of a single EEG channel and random forest classifier, Comput Methods Programs Biomed, 108, 10, 10.1016/j.cmpb.2011.11.005 Acharya, 2010, Analysis and automatic identification of sleep stages using higher order spectra, Int J Neural Syst, 20, 509, 10.1142/S0129065710002589 Bajaj, 2013, Automatic classification of sleep stages based on the time–frequency image of EEG signals, Comput Methods Programs Biomed, 112, 320, 10.1016/j.cmpb.2013.07.006 Herrera, 2013, Combination of heterogeneous EEG feature extraction methods and stacked sequential learning for sleep stage classification, Int J Neural Syst, 23, 1350012, 10.1142/S0129065713500123 Rodríguez-Sotelo, 2014, Automatic sleep stages classification using EEG entropy features and unsupervised pattern analysis techniques, Entropy, 16, 6573, 10.3390/e16126573 Liang, 2012, Automatic stage scoring of single-channel sleep EEG by using multiscale entropy and autoregressive models, IEEE Trans Instrum Meas, 61, 1649, 10.1109/TIM.2012.2187242 Liang, 2015, Development of an EOG-based automatic sleep-monitoring eye mask, IEEE Trans Instrum Meas, 64, 2977, 10.1109/TIM.2015.2433652 Hsu, 2013, Automatic sleep stage recurrent neural classifier using energy features of EEG signals, Neurocomputing, 104, 105, 10.1016/j.neucom.2012.11.003 Flexer, 2005, A reliable probabilistic sleep stager based on a single EEG signal, Artif Intell Med, 33, 199, 10.1016/j.artmed.2004.04.004 Doroshenkov, 2007, Classification of human sleep stages based on EEG processing using hidden Markov models, Biomed Eng, 41, 25, 10.1007/s10527-007-0006-5 Adnane, 2012, Sleep–wake stages classification and sleep efficiency estimation using single-lead electrocardiogram, Expert Syst Appl, 39, 1401, 10.1016/j.eswa.2011.08.022 Wu, 2015, Assess sleep stage by modern signal processing techniques, IEEE Trans Biomed Eng, 62, 1159, 10.1109/TBME.2014.2375292 Lajnef, 2015, Learning machines and sleeping brains: automatic sleep stage classification using decision-tree multi-class support vector machines, J Neurosci Methods, 250, 94, 10.1016/j.jneumeth.2015.01.022 Sousa, 2015, A two-step automatic sleep stage classification method with dubious range detection, Comput Biol Med, 59, 42, 10.1016/j.compbiomed.2015.01.017 Voss, 2004, Functions of sleep architecture and the concept of protective fields, Rev Neurosci, 15, 33, 10.1515/REVNEURO.2004.15.1.33 Kemp, 2000, Analysis of a sleep-dependent neuronal feedback loop: the slow-wave microcontinuity of the EEG, IEEE Trans Biomed Eng, 47, 1185, 10.1109/10.867928 Goldberger, 2000, PhysioBank, PhysioToolkit, and PhysioNet: components of a new research resource for complex physiologic signals, Circulation, 101, e215, 10.1161/01.CIR.101.23.e215 Costa, 2002, Multiscale entropy analysis of complex physiologic time series, Phys Rev Lett, 89, 068102, 10.1103/PhysRevLett.89.068102 Costa, 2005, Multiscale entropy analysis of biological signals, Phys Rev E, 71, 021906, 10.1103/PhysRevE.71.021906 Burioka, 2005, Approximate entropy in the electroencephalogram during wake and sleep, Clin EEG Neurosci, 36, 21, 10.1177/155005940503600106 Vapnik, 2013 Chang, 2011, LIBSVM: a library for support vector machines, ACM Trans Intell Syst Technol, 2, 27, 10.1145/1961189.1961199 Ronzhina, 2012, Sleep scoring using artificial neural networks, Sleep Med Rev, 16, 251, 10.1016/j.smrv.2011.06.003 Zhu, 2014, Analysis and classification of sleep stages based on difference visibility graphs from a single-channel EEG signal, IEEE J Biomed Health Inform, 18, 1813, 10.1109/JBHI.2014.2303991 Hassan, 2015, On the classification of sleep states by means of statistical and spectral features from single channel electroencephalogram, 2238