Real-time detection of REM phases with EEG records

• Autorzy: Bequart Valentin , Fermaut Luc , Fertin Milan , Robillart Julie , Kotas Rafał
• Języki publikacji: EN

Abstrakty

EN

The article presents the development of a program capable of real-time detection of REM phases during the human sleep. For this purpose, 39 electroencephalogram (EEG) recordings from PhysioNet were used. To achieve the goal of the project authors selected following set of parameters: the average amplitude of the signal, alpha and delta power band in frequency domain and the ratio Alpha-Delta, for 30 second interval. An Artificial Intelligence (AI) has been developed with Keras and trained with those parameters for 34 patients. Finally, the AI has been tested on the last 5 patients, by simulating a true night. It reaches 62% in sensibility for REM Phase detection, and 85% in specificity. Obtained results are promising in terms of real-time REM phase detection, but the approach needs further development.

Słowa kluczowe

EN

EEG; REM sleep; NREM sleep; artificial neural network

PL

EEG; sen REM; sen NREM; sztuczna sieć neuronowa

• Wydawca: Lodz University of Technology. Department of Microelectronics and Computer Science
• Czasopismo: International Journal of Microelectronics and Computer Science
• Rocznik: 2018
• Tom: Vol. 9, nr 4
• Strony: 155--160
• Opis fizyczny: Bibliogr. 14 poz., wykr.

Twórcy

autor

Bequart Valentin

• ISEN Lille Engineering School. 41 boulevard Yauban, 59046 Lille Cedex. France

autor

Fermaut Luc

• ISEN Lille Engineering School. 41 boulevard Yauban, 59046 Lille Cedex. France

autor

Fertin Milan

• ISEN Lille Engineering School. 41 boulevard Yauban, 59046 Lille Cedex. France

autor

Robillart Julie

• ISEN Lille Engineering School. 41 boulevard Yauban, 59046 Lille Cedex. France

autor

Kotas Rafał

• Department of Microelectronics and Computer Science. Lodz University of Technology, ul. Wólczańska 221/223, 90-924 Lodz. Poland

Bibliografia

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• [2] National Heart, Lung, and Blood Institute: Why Is Sleep Important? - Sleep Deprivation and Deficiency, Retrieved from https://www.nhlbi.aih.gov/node/4605 (2018, July 23)
• [3] Sound Sleep Health: What Stage of Sleep Is Most Important? NREM vs REM Sleep. Retrieved from https://www.soundsleephealth.coin/blog/ what-stage-of-sleep-is-most-important-nrem-vs-rem-sleep (2018, July 23)
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• [5] Aserinsky E, Kleitman N., Regularly occurring periods of eye motility and concomitant phenomena during sleep. Science 1953; 118: 273-274
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• [7] Estrada E, Nazeran H. Nava P, Behbehani K, Burk J, Lucas E. EEG feature extraction for classification of sleep stages, The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, San Francisco, CA, 2004, pp 196-199
• [8] Goldberger AL, Amaral LAN, Glass L, Hausdorff JM, Ivanov PCh, Mark RG, Mietus JE, Moody GB, Peng C-K, Stanley HE. PhysioBank, PhysioToolkit, and PhysioNet: Components of a New Research Resource for Complex Physiologic Signals. Circulation 101(23):e215-e220; 2000
• [9] Kemp B, Olivan J. European data format 'plus' (EDF+). an EDF alike standard format for the exchange of physiological data. Clin Neurophysiol. 2003 Sep:114(9):1755-61.
• [10] DennisDean, EDF Reader in Matlab; Retrieved from https://github.com/DennisDean/BlockEdfLoad (2018, July 23)
• [11] EDF Reader in Java (used for reading hypnograms): Retrieved from https://github.com/MIOB/EDF4J (2018, July 23)
• [12] Matlab Control from Java: Retrieved from https://code.google.eom/archive/p/matlabcontrol/ (2018, July 23)
• [13] Keras Documentation, Retrieved from https:/keras.iо/ (2018, July 23)
• [14] Lund HG, et al. Sleep patterns and predictors of disturbed sleep in a large population of college students. Journal of adolescent health 46.2 (2010): 124-132.

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).