<abstract xmlns="http://www.w3.org/1999/xhtml"><p>Sleep apnea is a growing sleep disorder issue and estimate to affect 7% of the adult population in Malaysia. In this study, the electrical activity of the brain is studied using Electroencephalogram (EEG). The data obtained was then decomposed using three methods; Empirical Mode Decomposition (EMD), Bivariate EMD and finally Ensemble EMD. The Index of Orthogonatility (IO) was obtained which shows EMD performed the most poorly, EEMD the best and Bivariate in between. The performance of EMD greatly improves when the number of samples was greatly decreased and very high peaks and more complex parts of the signal were excluded in the analysis. Segmentation was also conducted and the segmentation error revealed when an Event Related Potential (ERP) has happened which is when apnea occurred.</p></abstract>

Sleep apnea is a growing sleep disorder issue and estimate to affect 7% of the adult population in Malaysia. In this study, the electrical activity of the brain is studied using Electroencephalogram (EEG). The data obtained was then decomposed using three methods; Empirical Mode Decomposition (EMD), Bivariate EMD and finally Ensemble EMD. The Index of Orthogonatility (IO) was obtained which shows EMD performed the most poorly, EEMD the best and Bivariate in between. The performance of EMD greatly improves when the number of samples was greatly decreased and very high peaks and more complex parts of the signal were excluded in the analysis. Segmentation was also conducted and the segmentation error revealed when an Event Related Potential (ERP) has happened which is when apnea occurred.

Features Of Sleep Apnea Recognition And Analysis

International Journal on Smart Sensing and Intelligent Systems

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

{"article-title":"Features Of Sleep Apnea Recognition And Analysis"}

Sleep apnea is a growing sleep disorder issue and estimate to affect 7% of the adult population in Malaysia. In this study, the electrical activity of the...

Features Of Sleep Apnea Recognition And Analysis

Online veröffentlicht: 27. Dez. 2017

Seitenbereich: 481 - 497

Eingereicht: 15. Feb. 2014

Akzeptiert: 01. Juni 2014

DOI: https://doi.org/10.21307/ijssis-2017-666

Schlüsselwörter
Sleep apnea, Electroencephalogram (EEG), Empirical Mode Decomposition (EMD), Bivariate EMD, Ensemble EMD

© 2014 Leong Wai Yie et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Features Of Sleep Apnea Recognition And Analysis

Online veröffentlicht: 27. Dez. 2017

Seitenbereich: 481 - 497

Eingereicht: 15. Feb. 2014

Akzeptiert: 01. Juni 2014

DOI: https://doi.org/10.21307/ijssis-2017-666

SchlüsselwörterSleep apnea, Electroencephalogram (EEG), Empirical Mode Decomposition (EMD), Bivariate EMD, Ensemble EMD

© 2014 Leong Wai Yie et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Schlüsselwörter
Sleep apnea, Electroencephalogram (EEG), Empirical Mode Decomposition (EMD), Bivariate EMD, Ensemble EMD