Sleep monitoring classification strategy for an unobtrusive EEG system

J. Gialelis, C. Panagiotou, D. Karadimas, I. Samaras, P. Chondros, D. Serpanos, S. Koubias

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

1 Citation (Scopus)

Abstract

The advances in the wearable devices and Artificial Intelligence domains highlight the need for ICT systems that aim in the improvement of human's quality of life. In this paper we present the sleeping tracking component of an activity and sleeping tracking system. We present the sleep quality assessment based on EEG processing and support vector machines with sequential minimal optimization classifiers (SVM-SMO). The performance of the system demonstrated by respective experiments (accuracy: 83% and kappa coeff: 72%) exhibits significant prospects for the assessment of sleep quality and the further validation through an evaluation study.

Original languageEnglish
Title of host publicationProceedings - 2015 4th Mediterranean Conference on Embedded Computing, MECO 2015 - Including ECyPS 2015, BioEMIS 2015, BioICT 2015, MECO-Student Challenge 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages402-406
Number of pages5
ISBN (Print)9781479989997
DOIs
Publication statusPublished - 6 Aug 2015
Externally publishedYes
Event4th Mediterranean Conference on Embedded Computing, MECO 2015 - Budva, Montenegro
Duration: 14 Jun 201518 Jun 2015

Other

Other4th Mediterranean Conference on Embedded Computing, MECO 2015
CountryMontenegro
CityBudva
Period14/6/1518/6/15

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Keywords

  • EEG
  • sleep stages
  • SVM

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Hardware and Architecture
  • Control and Systems Engineering
  • Computer Science Applications

Cite this

Gialelis, J., Panagiotou, C., Karadimas, D., Samaras, I., Chondros, P., Serpanos, D., & Koubias, S. (2015). Sleep monitoring classification strategy for an unobtrusive EEG system. In Proceedings - 2015 4th Mediterranean Conference on Embedded Computing, MECO 2015 - Including ECyPS 2015, BioEMIS 2015, BioICT 2015, MECO-Student Challenge 2015 (pp. 402-406). [7181955] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/MECO.2015.7181955