Classification of healthy and insomnia subjects based on wake-To-sleep transition

C. Dissanyaka, D. Cvetkovic, H. Abdullah, Beena Ahmed, T. Penzel

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

Abstract

This study is carried out with the aim of classifying healthy and insomniac subjects based on their wake-To-sleep transition (sleep onset process) features. The features were extracted from those signals using non-parametric and parametric methods in frequency domain. Wavelet transform was used to calculate non-parametric features: relative power of EEG sub bands (delta, theta, alpha, beta and gamma). After that Sleep onset reference epochs were determined using first and last intersection of delta and alpha respectively. The statistical analysis was applied on the features obtained. The data was divided into two groups: Training data and testing data. Classification tree model was executed on training data to predict the healthy and insomniac groups in test data. K-fold cross-validation method was used for this estimation.

Original languageEnglish
Title of host publicationIECBES 2016 - IEEE-EMBS Conference on Biomedical Engineering and Sciences
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages480-483
Number of pages4
ISBN (Electronic)9781467377911
DOIs
Publication statusPublished - 3 Feb 2017
Event2016 IEEE-EMBS Conference on Biomedical Engineering and Sciences, IECBES 2016 - Kuala Lumpur, Malaysia
Duration: 4 Dec 20168 Dec 2016

Other

Other2016 IEEE-EMBS Conference on Biomedical Engineering and Sciences, IECBES 2016
CountryMalaysia
CityKuala Lumpur
Period4/12/168/12/16

Fingerprint

insomnia
sleep
wakes
education
electroencephalography
Electroencephalography
classifying
wavelet analysis
statistical analysis
intersections
Wavelet transforms
Statistical methods
time measurement
Testing
Sleep

Keywords

  • Classification TreeNormalised Mean Square Error (NMSE)
  • Electroencephalogram (EEG)
  • Sleep Onset Process (SOP)

ASJC Scopus subject areas

  • Biomedical Engineering
  • Instrumentation

Cite this

Dissanyaka, C., Cvetkovic, D., Abdullah, H., Ahmed, B., & Penzel, T. (2017). Classification of healthy and insomnia subjects based on wake-To-sleep transition. In IECBES 2016 - IEEE-EMBS Conference on Biomedical Engineering and Sciences (pp. 480-483). [7843497] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IECBES.2016.7843497

Classification of healthy and insomnia subjects based on wake-To-sleep transition. / Dissanyaka, C.; Cvetkovic, D.; Abdullah, H.; Ahmed, Beena; Penzel, T.

IECBES 2016 - IEEE-EMBS Conference on Biomedical Engineering and Sciences. Institute of Electrical and Electronics Engineers Inc., 2017. p. 480-483 7843497.

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

Dissanyaka, C, Cvetkovic, D, Abdullah, H, Ahmed, B & Penzel, T 2017, Classification of healthy and insomnia subjects based on wake-To-sleep transition. in IECBES 2016 - IEEE-EMBS Conference on Biomedical Engineering and Sciences., 7843497, Institute of Electrical and Electronics Engineers Inc., pp. 480-483, 2016 IEEE-EMBS Conference on Biomedical Engineering and Sciences, IECBES 2016, Kuala Lumpur, Malaysia, 4/12/16. https://doi.org/10.1109/IECBES.2016.7843497
Dissanyaka C, Cvetkovic D, Abdullah H, Ahmed B, Penzel T. Classification of healthy and insomnia subjects based on wake-To-sleep transition. In IECBES 2016 - IEEE-EMBS Conference on Biomedical Engineering and Sciences. Institute of Electrical and Electronics Engineers Inc. 2017. p. 480-483. 7843497 https://doi.org/10.1109/IECBES.2016.7843497
Dissanyaka, C. ; Cvetkovic, D. ; Abdullah, H. ; Ahmed, Beena ; Penzel, T. / Classification of healthy and insomnia subjects based on wake-To-sleep transition. IECBES 2016 - IEEE-EMBS Conference on Biomedical Engineering and Sciences. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 480-483
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