NDLI: Low-cost EEG-based sleep detection

Content Provider	IEEE Xplore Digital Library
Author	Van Hal, B. Rhodes, S. Dunne, B. Bossemeyer, R.
Copyright Year	2014
Description	Author affiliation: GE Aviation, Grand Rapids, MI, USA (Van Hal, B.) \|\| Sch. of Eng., Grand Valley State Univ., Grand Rapids, MI, USA (Rhodes, S.; Dunne, B.; Bossemeyer, R.)
Abstract	A real-time stage 1 sleep detection system using a low-cost single dry-sensor EEG headset is described. This device issues an auditory warning at the onset of stage 1 sleep using the “NeuroSky Mindset,” an inexpensive commercial entertainment-based headset. The EEG signal is filtered into low/high alpha and low/high beta frequency bands which are analyzed to indicate the onset of sleep. Preliminary results indicate an 81% effective rate of detecting sleep with all failures being false positives of sleep onset. This device was able to predict and respond to the onset of drowsiness preceding stage 1 sleep allowing for earlier warnings with the result of fewer sleep-related accidents.
Sponsorship	IEEE Eng. Med. Biol. Soc.
Starting Page	4571
Ending Page	4574
File Size	735801
Page Count	4
File Format	PDF
ISBN	9781424479290
ISSN	1557170X
DOI	10.1109/EMBC.2014.6944641
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-08-26
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Sleep Electroencephalography Radiation detectors Fatigue Electrodes Educational institutions Standards
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

Automatic sleep onset detection using single EEG sensor

Using NIRS as a predictor for EEG-based BCI performance

Automatic REM sleep detection associated with idiopathic rem sleep Behavior Disorder

Modular, bluetooth enabled, wireless electroencephalograph (EEG) platform

EEG-based brain connectivity analysis of states of unawareness

EEG signal features extraction based on fractal dimension

Reduction in time-to-sleep through EEG based brain state detection and audio stimulation

Parallel artefact rejection for epileptiform activity detection in routine EEG

Subject identification through standard EEG signals during resting states

Low-cost EEG-based sleep detection

Similar Documents

Automatic sleep onset detection using single EEG sensor

Using NIRS as a predictor for EEG-based BCI performance

Automatic REM sleep detection associated with idiopathic rem sleep Behavior Disorder

Modular, bluetooth enabled, wireless electroencephalograph (EEG) platform

EEG-based brain connectivity analysis of states of unawareness

EEG signal features extraction based on fractal dimension

Reduction in time-to-sleep through EEG based brain state detection and audio stimulation

Parallel artefact rejection for epileptiform activity detection in routine EEG

Subject identification through standard EEG signals during resting states

Low-cost EEG-based sleep detection