An automatic sleep spindle detector based on wavelets and the teager energy operator

Beena Ahmed, Amira Redissi, Reza Tafreshi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

33 Citations (Scopus)

Abstract

Sleep spindles are one of the most important short-lasting rhythmic events occurring in the EEG during Non-Rapid Eye Movement sleep. Their accurate identification in a polysomnographic signal is essential for sleep professionals to help them mark Stage 2 sleep. Visual spindle scoring however is a tedious workload, as there are often a thousand spindles in an all-night recording. In this paper a novel approach for the automatic detection of sleep spindles based upon the Teager Energy Operator and wavelet packets has been presented. The Teager operator was found to accurately enhance periodic activity in epochs of the EEG containing spindles. The wavelet packet transform proved effective in accurately locating spindles in the time-frequency domain. The autocorrelation function of the resultant Teager signal and the wavelet packet energy ratio were used to identify epochs with spindles. These two features were integrated into a spindle detection algorithm which achieved an accuracy of 93.7%.

Original languageEnglish
Title of host publicationProceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009
Pages2596-2599
Number of pages4
DOIs
Publication statusPublished - 2009
Event31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009 - Minneapolis, MN, United States
Duration: 2 Sep 20096 Sep 2009

Other

Other31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009
CountryUnited States
CityMinneapolis, MN
Period2/9/096/9/09

Fingerprint

Sleep
Detectors
Electroencephalography
Wavelet Analysis
Sleep Stages
Eye Movements
Workload
Eye movements
Autocorrelation

ASJC Scopus subject areas

  • Cell Biology
  • Developmental Biology
  • Biomedical Engineering
  • Medicine(all)

Cite this

Ahmed, B., Redissi, A., & Tafreshi, R. (2009). An automatic sleep spindle detector based on wavelets and the teager energy operator. In Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009 (pp. 2596-2599). [5335331] https://doi.org/10.1109/IEMBS.2009.5335331

An automatic sleep spindle detector based on wavelets and the teager energy operator. / Ahmed, Beena; Redissi, Amira; Tafreshi, Reza.

Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009. 2009. p. 2596-2599 5335331.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Ahmed, B, Redissi, A & Tafreshi, R 2009, An automatic sleep spindle detector based on wavelets and the teager energy operator. in Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009., 5335331, pp. 2596-2599, 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009, Minneapolis, MN, United States, 2/9/09. https://doi.org/10.1109/IEMBS.2009.5335331
Ahmed B, Redissi A, Tafreshi R. An automatic sleep spindle detector based on wavelets and the teager energy operator. In Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009. 2009. p. 2596-2599. 5335331 https://doi.org/10.1109/IEMBS.2009.5335331
Ahmed, Beena ; Redissi, Amira ; Tafreshi, Reza. / An automatic sleep spindle detector based on wavelets and the teager energy operator. Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009. 2009. pp. 2596-2599
@inproceedings{21e82d0e380247a6a06f10f416c2886c,
title = "An automatic sleep spindle detector based on wavelets and the teager energy operator",
abstract = "Sleep spindles are one of the most important short-lasting rhythmic events occurring in the EEG during Non-Rapid Eye Movement sleep. Their accurate identification in a polysomnographic signal is essential for sleep professionals to help them mark Stage 2 sleep. Visual spindle scoring however is a tedious workload, as there are often a thousand spindles in an all-night recording. In this paper a novel approach for the automatic detection of sleep spindles based upon the Teager Energy Operator and wavelet packets has been presented. The Teager operator was found to accurately enhance periodic activity in epochs of the EEG containing spindles. The wavelet packet transform proved effective in accurately locating spindles in the time-frequency domain. The autocorrelation function of the resultant Teager signal and the wavelet packet energy ratio were used to identify epochs with spindles. These two features were integrated into a spindle detection algorithm which achieved an accuracy of 93.7{\%}.",
author = "Beena Ahmed and Amira Redissi and Reza Tafreshi",
year = "2009",
doi = "10.1109/IEMBS.2009.5335331",
language = "English",
isbn = "9781424432967",
pages = "2596--2599",
booktitle = "Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009",

}

TY - GEN

T1 - An automatic sleep spindle detector based on wavelets and the teager energy operator

AU - Ahmed, Beena

AU - Redissi, Amira

AU - Tafreshi, Reza

PY - 2009

Y1 - 2009

N2 - Sleep spindles are one of the most important short-lasting rhythmic events occurring in the EEG during Non-Rapid Eye Movement sleep. Their accurate identification in a polysomnographic signal is essential for sleep professionals to help them mark Stage 2 sleep. Visual spindle scoring however is a tedious workload, as there are often a thousand spindles in an all-night recording. In this paper a novel approach for the automatic detection of sleep spindles based upon the Teager Energy Operator and wavelet packets has been presented. The Teager operator was found to accurately enhance periodic activity in epochs of the EEG containing spindles. The wavelet packet transform proved effective in accurately locating spindles in the time-frequency domain. The autocorrelation function of the resultant Teager signal and the wavelet packet energy ratio were used to identify epochs with spindles. These two features were integrated into a spindle detection algorithm which achieved an accuracy of 93.7%.

AB - Sleep spindles are one of the most important short-lasting rhythmic events occurring in the EEG during Non-Rapid Eye Movement sleep. Their accurate identification in a polysomnographic signal is essential for sleep professionals to help them mark Stage 2 sleep. Visual spindle scoring however is a tedious workload, as there are often a thousand spindles in an all-night recording. In this paper a novel approach for the automatic detection of sleep spindles based upon the Teager Energy Operator and wavelet packets has been presented. The Teager operator was found to accurately enhance periodic activity in epochs of the EEG containing spindles. The wavelet packet transform proved effective in accurately locating spindles in the time-frequency domain. The autocorrelation function of the resultant Teager signal and the wavelet packet energy ratio were used to identify epochs with spindles. These two features were integrated into a spindle detection algorithm which achieved an accuracy of 93.7%.

UR - http://www.scopus.com/inward/record.url?scp=77950999326&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=77950999326&partnerID=8YFLogxK

U2 - 10.1109/IEMBS.2009.5335331

DO - 10.1109/IEMBS.2009.5335331

M3 - Conference contribution

SN - 9781424432967

SP - 2596

EP - 2599

BT - Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009

ER -