A novel insomnia identification method based on Hjorth parameters

Sana Tmar Ben Hamida, Beena Ahmed, Thomas Penzel

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

4 Citations (Scopus)

Abstract

In this work, we present a &-means classifier using Hjorth parameters extracted from the central electroencephalogram (EEG) signals to accurately detect insomnia. To develop and test our classifier we used data from thirty six subjects: 18 patients diagnosed with primary insomnia (10 females, 8 males) and 18 controls (10 females, 8 males). The main findings of our work can be summarized as follows: 1) the Hjorth parameters, particularly the mobility and the complexity, accurately quantify the differences between the EEG sleep from insomnia patients and controls; 2) these differences can be observed across both C3 and C4 central channels; and 3) a k-means classifier based on Hjorth parameters extracted from the C3 channel is able to accurately detect epochs from insomnia patients with a Cohen's Kappa of 0.83, sensitivity of 91.9% and specificity of 91%.

Original languageEnglish
Title of host publication2015 IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages548-552
Number of pages5
ISBN (Electronic)9781509004805
DOIs
Publication statusPublished - 28 Jan 2016
Event15th IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2015 - Abu Dhabi, United Arab Emirates
Duration: 7 Dec 201510 Dec 2015

Other

Other15th IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2015
CountryUnited Arab Emirates
CityAbu Dhabi
Period7/12/1510/12/15

Fingerprint

Classifiers
Electroencephalography
Sleep

Keywords

  • Hjorth parameters
  • k-means clustering
  • sleep signal analysis

ASJC Scopus subject areas

  • Signal Processing

Cite this

Hamida, S. T. B., Ahmed, B., & Penzel, T. (2016). A novel insomnia identification method based on Hjorth parameters. In 2015 IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2015 (pp. 548-552). [7394397] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISSPIT.2015.7394397

A novel insomnia identification method based on Hjorth parameters. / Hamida, Sana Tmar Ben; Ahmed, Beena; Penzel, Thomas.

2015 IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2015. Institute of Electrical and Electronics Engineers Inc., 2016. p. 548-552 7394397.

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

Hamida, STB, Ahmed, B & Penzel, T 2016, A novel insomnia identification method based on Hjorth parameters. in 2015 IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2015., 7394397, Institute of Electrical and Electronics Engineers Inc., pp. 548-552, 15th IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2015, Abu Dhabi, United Arab Emirates, 7/12/15. https://doi.org/10.1109/ISSPIT.2015.7394397
Hamida STB, Ahmed B, Penzel T. A novel insomnia identification method based on Hjorth parameters. In 2015 IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2015. Institute of Electrical and Electronics Engineers Inc. 2016. p. 548-552. 7394397 https://doi.org/10.1109/ISSPIT.2015.7394397
Hamida, Sana Tmar Ben ; Ahmed, Beena ; Penzel, Thomas. / A novel insomnia identification method based on Hjorth parameters. 2015 IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2015. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 548-552
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