Literature DB >> 21107745

Objective measure of sleepiness and sleep latency via bispectrum analysis of EEG.

Vinayak Swarnkar1, Udantha Abeyratne, Craig Hukins.   

Abstract

Chronic sleepiness is a common symptom in the sleep disorders, such as, Obstructive Sleep Apnea, Periodic leg movement disorder, narcolepsy, etc. It affects 8% of the adult population and is associated with significant morbidity and increased risk to individual and society. MSLT and MWT are the existing tests for measuring sleepiness. Sleep Latency (SL) is the main measures of sleepiness computed in these tests. These are the laboratory-based tests and require services of an expert sleep technician. There are no tests available to detect inadvertent sleep onset in real time and which can be performed in any professional work environment to measure sleepiness level. In this article, we propose a fully automated, objective sleepiness analysis technique based on the single channel of EEG. The method uses a one-dimensional slice of the EEG Bispectrum representing a nonlinear transformation of the underlying EEG generator to compute a novel index called Sleepiness Index. The SL is then computed from the SI. Working on the patient's database of 42 subjects we computed SI and estimated SL. A strong significant correlation (r ≥ 0.70, s < 0.001) was found between technician scored SL and that computed via SI. The proposed technology holds promise in the automation of the MSLT and MWT tests. It can also be developed into a sleep management system, wherein the SI is incorporated into a sleepiness index alert unit to alarm the user when sleepiness level crosses the predetermined threshold.

Entities:  

Mesh:

Year:  2010        PMID: 21107745     DOI: 10.1007/s11517-010-0715-x

Source DB:  PubMed          Journal:  Med Biol Eng Comput        ISSN: 0140-0118            Impact factor:   2.602


  25 in total

1.  Mixed-phase modeling in snore sound analysis.

Authors:  Udantha R Abeyratne; Asela S Karunajeewa; Craig Hukins
Journal:  Med Biol Eng Comput       Date:  2007-07-12       Impact factor: 2.602

2.  On arousal from sleep: time-frequency analysis.

Authors:  M O Mendez; A M Bianchi; N Montano; V Patruno; E Gil; C Mantaras; S Aiolfi; S Cerutti
Journal:  Med Biol Eng Comput       Date:  2008-02-12       Impact factor: 2.602

3.  Higher-order spectral analysis of burst patterns in EEG.

Authors:  J Muthuswamy; D L Sherman; N V Thakor
Journal:  IEEE Trans Biomed Eng       Date:  1999-01       Impact factor: 4.538

4.  Guidelines for the multiple sleep latency test (MSLT): a standard measure of sleepiness.

Authors:  M A Carskadon; W C Dement; M M Mitler; T Roth; P R Westbrook; S Keenan
Journal:  Sleep       Date:  1986-12       Impact factor: 5.849

Review 5.  Catastrophes, sleep, and public policy: consensus report.

Authors:  M M Mitler; M A Carskadon; C A Czeisler; W C Dement; D F Dinges; R C Graeber
Journal:  Sleep       Date:  1988-02       Impact factor: 5.849

6.  Excessive daytime sleepiness in a general population sample: the role of sleep apnea, age, obesity, diabetes, and depression.

Authors:  E O Bixler; A N Vgontzas; H-M Lin; S L Calhoun; A Vela-Bueno; A Kales
Journal:  J Clin Endocrinol Metab       Date:  2005-06-07       Impact factor: 5.958

7.  Scoring variability between polysomnography technologists in different sleep laboratories.

Authors:  Nancy A Collop
Journal:  Sleep Med       Date:  2002-01       Impact factor: 3.492

8.  A new method for measuring daytime sleepiness: the Epworth sleepiness scale.

Authors:  M W Johns
Journal:  Sleep       Date:  1991-12       Impact factor: 5.849

9.  New tracheal sound feature for apnoea analysis.

Authors:  A Kulkas; E Huupponen; J Virkkala; M Tenhunen; A Saastamoinen; E Rauhala; S-L Himanen
Journal:  Med Biol Eng Comput       Date:  2009-02-11       Impact factor: 2.602

10.  Evaluation of automated and semi-automated scoring of polysomnographic recordings from a clinical trial using zolpidem in the treatment of insomnia.

Authors:  Vladimir Svetnik; Junshui Ma; Keith A Soper; Scott Doran; John J Renger; Steve Deacon; Ken S Koblan
Journal:  Sleep       Date:  2007-11       Impact factor: 5.849

View more
  7 in total

1.  Engineering better sleep.

Authors:  Ronald D Chervin; Joseph W Burns
Journal:  Med Biol Eng Comput       Date:  2011-04-13       Impact factor: 2.602

2.  FASTER: an unsupervised fully automated sleep staging method for mice.

Authors:  Genshiro A Sunagawa; Hiroyoshi Séi; Shigeki Shimba; Yoshihiro Urade; Hiroki R Ueda
Journal:  Genes Cells       Date:  2013-04-28       Impact factor: 1.891

3.  Detection of driver drowsiness using wavelet analysis of heart rate variability and a support vector machine classifier.

Authors:  Gang Li; Wan-Young Chung
Journal:  Sensors (Basel)       Date:  2013-12-02       Impact factor: 3.576

4.  Estimation of eye closure degree using EEG sensors and its application in driver drowsiness detection.

Authors:  Gang Li; Wan-Young Chung
Journal:  Sensors (Basel)       Date:  2014-09-18       Impact factor: 3.576

Review 5.  Electroencephalogram-Based Approaches for Driver Drowsiness Detection and Management: A Review.

Authors:  Gang Li; Wan-Young Chung
Journal:  Sensors (Basel)       Date:  2022-01-31       Impact factor: 3.576

Review 6.  The Application of Electroencephalogram in Driving Safety: Current Status and Future Prospects.

Authors:  Yong Peng; Qian Xu; Shuxiang Lin; Xinghua Wang; Guoliang Xiang; Shufang Huang; Honghao Zhang; Chaojie Fan
Journal:  Front Psychol       Date:  2022-07-22

7.  A Context-Aware EEG Headset System for Early Detection of Driver Drowsiness.

Authors:  Gang Li; Wan-Young Chung
Journal:  Sensors (Basel)       Date:  2015-08-21       Impact factor: 3.576

  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.