Sleep stage classification of sleep apnea patients using decision-tree-based support vector machines based on ECG parameters

Jeen Shing Wang, Guan Rong Shih, Wei Chun Chiang

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

14 Citations (Scopus)

Abstract

This paper describes the design and validation of an effective sleep stage classification strategy for patients with sleep apnea. This strategy consists of a sequential forward selection (SFS) feature selection method and a decision-tree-based support vector machines (DTB-SVM) classifier for discriminating three types of sleep based on electrocardiogram (ECG) signals. Each 5-minute epoch of ECG signal data collected during sleep was used to generate 24 features using heart rate variability (HRV) analysis. An SFS feature selection method was then employed to determine which significant features should be selected to improve classification accuracy. A DTB-SVM was then trained using selected features in order to discriminate three sleep stages, including pre-sleep wakefulness, NREM sleep and REM sleep. The average classification accuracy of the proposed strategy was 73.51%. Our experimental results demonstrate that the proposed strategy provides moderate accuracy for detecting sleep stages in sleep apnea patients and can serve as a convenient tool for assessing sleep quality.

Original languageEnglish
Title of host publicationProceedings - IEEE-EMBS International Conference on Biomedical and Health Informatics
Subtitle of host publicationGlobal Grand Challenge of Health Informatics, BHI 2012
Pages285-288
Number of pages4
DOIs
Publication statusPublished - 2012 Jul 30
EventIEEE-EMBS International Conference on Biomedical and Health Informatics, BHI 2012. In Conj. with the 8th Int. Symp.on Medical Devices and Biosensors and the 7th Int. Symp. on Biomedical and Health Engineering - Hong Kong and Shenzhen, China
Duration: 2012 Jan 22012 Jan 7

Publication series

NameProceedings - IEEE-EMBS International Conference on Biomedical and Health Informatics: Global Grand Challenge of Health Informatics, BHI 2012

Other

OtherIEEE-EMBS International Conference on Biomedical and Health Informatics, BHI 2012. In Conj. with the 8th Int. Symp.on Medical Devices and Biosensors and the 7th Int. Symp. on Biomedical and Health Engineering
Country/TerritoryChina
CityHong Kong and Shenzhen
Period12-01-0212-01-07

All Science Journal Classification (ASJC) codes

  • Biomedical Engineering
  • Health Informatics

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