Akbari H, Ghofrani S, Zakalvand P, Sadiq MT (2021) Schizophrenia recognition based on the phase space dynamic of EEG signals and graphical features. Biomed Signal Process Control 69:102917. https://doi.org/10.1016/j.bspc.2021.102917
Al-Salman W, Li Y, Oudah AY (2023) Almaged S (2023) Sleep stage classification in eeg signals using the clustering approach based probability distribution features coupled with classification algorithms. Neurosci Res 188:51–67
Article CAS PubMed Google Scholar
Arora A, Chakraborty P, Bhatia MPS (2020) Analysis of data from wearable sensors for sleep quality estimation and prediction using deep learning. Arabian J Sci Eng 45:10793–10812
Babiloni AH, Koninck BPD, Beetz G, Beaumont LD, Martel MO, Lavigne GJ (2020) Sleep and pain: recent insights, mechanisms, and future directions in the investigation of this relationship. J Neural Trans 127:647–660
Dhok S, Pimpalkhute V, Chandurkar A, Bhurane A, Sharma M, Acharya UR (2020) Automated phase classification in cyclic alternating patterns in sleep stages using Wigner-Ville distribution based features. Comput Biol Med. https://doi.org/10.1016/j.compbiomed.2020.103691
Dietterich TG (2004) An experimental comparison of three methods for constructing ensembles of decision trees: Bagging, boosting, and randomization. Mach Learning 40:139–157
Fatimah B, Singh P, Singhal A, Pachori RB (2020) Detection of apnea events from ECG segments using Fourier decomposition method. Biomed Signal Process Control 61:102005
Fernandez LMJ, Lüthi A (2020) Sleep spindles: Mechanisms and functions. Physiol Rev 100(2)
Gorgoni M, D’Atri A, Scarpelli S, Reda F, Gennaro LD (2020) Sleep electroencephalography and brain maturation: developmental trajectories and the relation with cognitive functioning. Sleep Med 66:33–50
Article CAS PubMed Google Scholar
Hartmann S, Baumert M (2019) Automatic A-phase detection of cyclic alternating patterns in sleep using dynamic temporal information. IEEE Trans Neural Syst Rehabil Eng 27(9):1–1. https://doi.org/10.1109/TNSRE.2019.2934828
Johannesen JK, Bi J, Jiang R, Kenney JG, Chen C-MA (2016) Machine learning identification of EEG features predicting working memory performance in schizophrenia and healthy adults. Neuropsych Electrophys. https://doi.org/10.1186/s40810-016-0017-0
Kales A, Rechtschaffen A (1968) L.A.B.I.S. University of California: A Manual of Standardized Terminology, Techniques and Scoring System for Sleep Stages of Human Subjects. In: Rechtschaffen A, Kales A (Eds.). NIH Publication, U. S. National Institute of Neurological Diseases and Blindness, Neurological Information Network. https://books.google.co.in/books?id=wzdRnQEACAAJ
Korkmaz S, Bilecenoglu NT, Aksu M, Yoldas TK (2018) Cyclic alternating pattern in obstructive sleep apnea patients with versus without excessive sleepiness. Sleep Disorders, 8713409
Koyanagi A, Stickley A (2015) The association between sleep problems and psychotic symptoms in the general population: a global perspective. Sleep 38:1875–1885
Article PubMed PubMed Central Google Scholar
Lashgari E, Liang D, Maoz U (2020) Data augmentation for deep-learning-based electroencephalography. J Neurosci Methods 346:108885
Liborio Parrino ACM (2014) Cyclic alternating pattern, 2014. https://www.medlink.com/index.php/article/cyclic_alternating_pattern. [accessed 26 March 2023]
Loh H, Ooi C, Dhok S, Sharma M, Bhurane A, Acharya UR (2022) Automated detection of cyclic alternating pattern and classification of sleep stages using deep neural network. Appl Intell. https://doi.org/10.1007/s10489-021-02597-8
Machado F, Sales F, Santos C, Dourado A, Teixeira CA (2018) A knowledge discovery methodology from EEG data for cyclic alternating pattern detection. Biomed Eng Online 17(1):185. https://doi.org/10.1186/s12938-018-0616-z
Article PubMed PubMed Central Google Scholar
Mariani S, Grassi A, Mendez M, Milioli G, Parrino L, Terzano M, Bianchi A (2013) EEG segmentation for improving automatic CAP detection. Clinical Neurophysiol. https://doi.org/10.1016/j.clinph.2013.04.005
Mariani S, Bianchi AM, Manfredini E, et al (2010) Automatic detection of A phases of the cyclic alternating pattern during sleep. In: 2010 annual international conference of the IEEE engineering in medicine and biology, pp. 5085–5088. https://doi.org/10.1109/IEMBS.2010.5626211
Mendez MO, Chouvarda I, Alba A, Bianchi AM, Grassi A, Arce-Santana E, Milioli G, Terzano MG, Parrino L (2016) Analysis of A-phase transitions during the cyclic alternating pattern under normal sleep. Med Biol Eng Comput 54(1):133–148. https://doi.org/10.1007/s11517-015-1349-9
Mendez MO, Alba A, Chouvarda I, Milioli G, Grassi A, Terzano MG, Parrino L (2014) On separability of A-phases during the cyclic alternating pattern. In: 36th annual international conference of the IEEE engineering in medicine and biology society, pp. 2253–2256. https://doi.org/10.1109/EMBC.2014.6944068
Mendonça F, Fred A, Mostafa S, Morgado-Dias F, García AG (2022) Automatic detection of cyclic alternating pattern. Neural Comput Appl. https://doi.org/10.1007/s00521-018-3474-5
Mendonça F, Mostafa SS, Freitas D, Morgado-Dias F, Ravelo-García AG (2022) Multiple time series fusion based on LSTM: An application to CAP A phase classification using EEG. Int J Environ Res Public Health 19(17):10892
Article PubMed PubMed Central Google Scholar
Migueis DP, Lopes MC, Ignacio PSD et al (2021) A systematic review and meta-analysis of the cyclic alternating pattern across the lifespan. Sleep Med 85:25–37
Article CAS PubMed Google Scholar
Mostafa SS, Mendonça F, Ravelo-García A, Morgado-Dias F (2018) Combination of deep and shallow networks for cyclic alternating patterns detection. In: 13th APCA international conference on automatic control and soft computing, pp. 98–103. https://doi.org/10.1109/CONTROLO.2018.8516418
Murarka S, Wadichar A, Bhurane A, Sharma M, Acharya UR (2022) Automated classification of cyclic alternating pattern sleep phases in healthy and sleep-disordered subjects using convolutional neural network. Comput Biol Med 146:105594. https://doi.org/10.1016/j.compbiomed.2022.105594
National Heart, Lung and Blood Institute (2019) Sleep deprivation and deficiency, https://www.nhlbi.nih.gov/health-topics/sleep-deprivation-and-deficiency. [accessed 26 March 2023]
Navona C, Barcaro U, Bonanni E, Martino FD, Maestri M, Murri L (2002) An automatic method for the recognition and classification of the A-phases of the cyclic alternating pattern. Clinical Neurophysiology 113:1826–1831
Parrino L, Ferri R, Bruni O, Terzano MG (2012) Cyclic alternating pattern (CAP): the marker of sleep instability. Sleep Med Rev 16(1):27–45. https://doi.org/10.1016/j.smrv.2011.02.003
Rahman MM, Bhuiyan MIH, Hassan AR (2018) Sleep stage classification using single-channel EOG. Comput Biol Med 102:211–220. https://doi.org/10.1016/j.compbiomed.2018.08.022
Sara M, Elena M, Valentina R et al (2012) Efficient automatic classifiers for the detection of A phases of the cyclic alternating pattern in sleep. Medical Biol Eng Comput 50(4):359–372
Sharma M, Patel S, Choudhary S, Acharya UR (2020) Automated detection of sleep stages using energy-localized orthogonal wavelet filter banks. Arabian J Sci Eng 45:2531–2544
Sharma M, Patel V, Tiwari J, Acharya UR (2021) Automated characterization of cyclic alternating pattern using wavelet-based features and ensemble learning techniques with EEG signals. Diagnostics 11(8):1380
Article PubMed PubMed Central Google Scholar
Singhal A, Singh P, Fatimah B, Pachori RB (2020) An efficient removal of power-line interference and baseline wander from ECG signals by employing Fourier decomposition technique. Biomed Signal Process Control 57:101741
Stranges S, Tigbe W, Gomez-Olive FX, Thorogood M, Kandala N-B (2012) Sleep problems: an emerging global epidemic? findings from the INDEPTH WHO-SAGE study among more than 40,000 older adults from 8 countries across africa and asia. Sleep 35:1173–1181
Article PubMed PubMed Central Google Scholar
Terzano MG, Parrino L (1993) Clinical applications of cyclic alternating pattern. Physiol Behav 54(4):807–813. https://doi.org/10.1016/0031-9384(93)90096-X
Article CAS PubMed Google Scholar
Terzano MG, Parrino L, Smerieri A (2001) Atlas, rules, and recording techniques for the scoring of cyclic alternating pattern (CAP) in human sleep. Sleep Med 2(6):537–53
Article CAS PubMed Google Scholar
Vargha A, Delaney HD (1998) The Kruskal-Wallis test and stochastic homogenity. J Edu Behavioral Stat 170–192
Yildirim O, Baloglu UB, Acharya UR (2019) A deep learning model for automated sleep stages classification using PSG signals. Int J Environ Res Public Health. https://doi.org/10.3390/ijerph16040599
Comments (0)