Automatic SLEEP staging: From young aduslts to elderly patients using multi-class support vector machine

Jacob Kempfner; Poul Jennum; Helge B. D. Sorensen; Julie A. E. Christensen; Miki Nikolic

doi:10.1109/EMBC.2013.6610864

Automatic SLEEP staging: From young aduslts to elderly patients using multi-class support vector machine

Jacob Kempfner, Poul Jennum, Helge B. D. Sorensen, Julie A. E. Christensen, Miki Nikolic

Copenhagen University Hospital Herlev and Gentofte

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Abstract

Aging is a process that is inevitable, and makes our body vulnerable to age-related diseases. Age is the most consistent factor affecting the sleep structure. Therefore, new automatic sleep staging methods, to be used in both of young and elderly patients, are needed. This study proposes an automatic sleep stage detector, which can separate wakefulness, rapid-eye-movement (REM) sleep and non-REM (NREM) sleep using only EEG and EOG. Most sleep events, which define the sleep stages, are reduced with age. This is addressed by focusing on the amplitude of the clinical EEG bands, and not the affected sleep events. The age-related influences are then reduced by robust subject-specific scaling. The classification of the three sleep stages are achieved by a multi-class support vector machine using the one-versus-rest scheme. It was possible to obtain a high classification accuracy of 0.91. Validation of the sleep stage detector in other sleep disorders, such as apnea and narcolepsy, should be considered in future work.

Original language	English
Title of host publication	2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Publisher	IEEE
Publication date	2013
Pages	5777 - 5780
ISBN (Print)	9781457702167
DOIs	https://doi.org/10.1109/EMBC.2013.6610864
Publication status	Published - 2013
Event	2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society - Oaska International Convention Center, Osaka, Japan Duration: 3 Jul 2013 → 7 Jul 2013 Conference number: 35 https://ieeexplore.ieee.org/xpl/conhome/6596169/proceeding

Conference

Conference	2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Number	35
Location	Oaska International Convention Center
Country/Territory	Japan
City	Osaka
Period	03/07/2013 → 07/07/2013
Internet address	https://ieeexplore.ieee.org/xpl/conhome/6596169/proceeding

Keywords

diseases
electro-oculography
electroencephalography
geriatrics
medical disorders
medical signal detection
signal classification
sleep
support vector machines
Engineered Materials, Dielectrics and Plasmas

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10.1109/EMBC.2013.6610864

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title = "Automatic SLEEP staging: From young aduslts to elderly patients using multi-class support vector machine",

abstract = "Aging is a process that is inevitable, and makes our body vulnerable to age-related diseases. Age is the most consistent factor affecting the sleep structure. Therefore, new automatic sleep staging methods, to be used in both of young and elderly patients, are needed. This study proposes an automatic sleep stage detector, which can separate wakefulness, rapid-eye-movement (REM) sleep and non-REM (NREM) sleep using only EEG and EOG. Most sleep events, which define the sleep stages, are reduced with age. This is addressed by focusing on the amplitude of the clinical EEG bands, and not the affected sleep events. The age-related influences are then reduced by robust subject-specific scaling. The classification of the three sleep stages are achieved by a multi-class support vector machine using the one-versus-rest scheme. It was possible to obtain a high classification accuracy of 0.91. Validation of the sleep stage detector in other sleep disorders, such as apnea and narcolepsy, should be considered in future work.",

keywords = "diseases, electro-oculography, electroencephalography, geriatrics, medical disorders, medical signal detection, signal classification, sleep, support vector machines, Engineered Materials, Dielectrics and Plasmas",

author = "Jacob Kempfner and Poul Jennum and Sorensen, {Helge B. D.} and Christensen, {Julie A. E.} and Miki Nikolic",

year = "2013",

doi = "10.1109/EMBC.2013.6610864",

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publisher = "IEEE",

address = "United States",

note = "2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013 ; Conference date: 03-07-2013 Through 07-07-2013",

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Kempfner, J, Jennum, P, Sorensen, HBD, Christensen, JAE & Nikolic, M 2013, Automatic SLEEP staging: From young aduslts to elderly patients using multi-class support vector machine. in 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society . IEEE, pp. 5777 - 5780 , 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Osaka, Japan, 03/07/2013. https://doi.org/10.1109/EMBC.2013.6610864

Automatic SLEEP staging: From young aduslts to elderly patients using multi-class support vector machine. / Kempfner, Jacob; Jennum, Poul; Sorensen, Helge B. D. et al.
2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society . IEEE, 2013. p. 5777 - 5780 .

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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AU - Nikolic, Miki

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KW - electroencephalography

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KW - signal classification

KW - sleep

KW - support vector machines

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Y2 - 3 July 2013 through 7 July 2013

ER -

Automatic SLEEP staging: From young aduslts to elderly patients using multi-class support vector machine

Abstract

Conference

Keywords

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