NDLI: Polysomnographic pattern recognition for automated classification of sleep-waking states in infants

Content Provider	Springer Nature Link
Author	Estévez, P. A. Held, C. M. Holzmann, C. A. Perez, C. A. Pérez, J. P. Heiss, J. Garrido, M. Peira, P.
Copyright Year	2002
Abstract	A robust, automated pattern recognition system for polysomnography data targeted to the sleep-waking state and stage identification is presented. Five patterns were searched for: slow-delta and theta wave predominance in the background electro-encephalogram (EEG) activity; presence of sleep spindles in the EEG; presence of rapid eye movements in an electro-oculogram; and presence of muscle tone in an electromyogram. The performance of the automated system was measured indirectly by evaluating sleep staging, based on the experts' accepted methodology, to relate the detected patterns in infants over four months of post-term age. The set of sleep-waking classes included wakefulness, REM sleep and non-REM sleep stages I, II, and III–IV. Several noise and artifact rejection methods were implemented, including filters, fuzzy quality indices, windows of variable sizes and detectors of limb movements and wakefulness. Eleven polysomnographic recordings of healthy infants were studied. The ages of the subjects ranged from 6 to 13 months old. Six recordings counting 2665 epochs were included in the training set. Results on a test set (2369 epochs from five recordings) show an overall agreement of 87.7% (kappa 0.840) between the automated system and the human expert. These results show significant improvements compared with previous work.
Starting Page	105
Ending Page	113
Page Count	9
File Format	PDF
ISSN	01400118
Journal	Medical and Biological Engineering and Computing
Volume Number	40
Issue Number	1
e-ISSN	17410444
Language	English
Publisher	Springer-Verlag
Publisher Date	2002-01-01
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Sleep analysis Pattern recognition Sleep-waking states Sleep-waking classification Fuzzy sets Polysomnography Human Physiology Computer Applications Neurosciences Imaging Radiology Biomedical Engineering
Content Type	Text
Resource Type	Article
Subject	Biomedical Engineering Computer Science Applications

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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