NDLI: Automated detection of Rapid Eye Movements in children

Content Provider	IEEE Xplore Digital Library
Author	Held, C.M. Causa, J. Causa, L. Estevez, P.A. Perez, C.A. Garrido, M. Chamorro, R. Algarin, C. Peirano, P.
Copyright Year	2012
Description	Author affiliation: Sleep Lab., Univ. de Chile, Santiago, Chile (Garrido, M.; Chamorro, R.; Algarin, C.; Peirano, P.) \|\| Dept. of Electr. Eng., Univ. de Chile, Santiago, Chile (Held, C.M.; Causa, J.; Causa, L.; Estevez, P.A.; Perez, C.A.)
Abstract	We present an automated multiple-step tool to identify Rapid Eye Movements (REMs) in the polysomnogram, based on modeling expert criteria. It begins by identifying the polysomnogram segments compatible with REMs presence. On these segments, high-energy REMs are identified. Then, vicinity zones around those REMs are defined, and lesser-energy REMs are sought in these vicinities. This strategy has the advantage that it can detect lesser-energy REMs without increasing much the false positive detections. Signal processing, feature extraction, and fuzzy logic tools are used to achieve the goal. The tool was trained and validated on a database consisting of 20 all-night polysomnogram recordings (160 hr) of healthy ten-year-old children. Preliminary results on the validation set show 85.5% sensitivity and a false positive rate of 16.2%. Our tool works on complete polysomnogram recordings, without the need of preprocessing, prior knowledge of the hypnogram, or noise-free segments selection.
Sponsorship	IEEE Eng. Medicine Biol. Soc.
Starting Page	2267
Ending Page	2270
File Size	1098012
Page Count	4
File Format	PDF
ISBN	9781424441198
ISSN	1557170X
e-ISBN	9781457717871
DOI	10.1109/EMBC.2012.6346414
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-08-28
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	MATLAB Indexes Training Sleep
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

Sl.	Authority	Responsibilities	Communication Details
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
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Detection of sleep disordered breathing by automated ECG analysis

Automated Sleep Spindle detection using novel EEG features and mixture models

Detection of post apnea sounds and apnea periods from sleep sounds

Development of a sleep apnea event detection method using photoplethysmography

Automated detection of apnea/hypopnea events in healthy children polysomnograms: Preliminary results

Characterization of movements during restless sleep in children: A pilot study

Design of experiments in Biomedical Signal Processing course

Gaussian model for movement detection during Sleep

Drowsiness detection by thoracic effort signal analysis in real driving environments

Automated detection of Rapid Eye Movements in children

Similar Documents

Detection of sleep disordered breathing by automated ECG analysis

Automated Sleep Spindle detection using novel EEG features and mixture models

Detection of post apnea sounds and apnea periods from sleep sounds

Development of a sleep apnea event detection method using photoplethysmography

Automated detection of apnea/hypopnea events in healthy children polysomnograms: Preliminary results

Characterization of movements during restless sleep in children: A pilot study

Design of experiments in Biomedical Signal Processing course

Gaussian model for movement detection during Sleep

Drowsiness detection by thoracic effort signal analysis in real driving environments

Automated detection of Rapid Eye Movements in children