Automatic sleep scoring using statistical features in the EMD domain and ensemble methods

• Autorzy: Hassan A. R. , Bhuiyan M. I. H.

Identyfikatory

DOI

10.1016/j.bbe.2015.11.001

• Języki publikacji: EN

Abstrakty

EN

An automatic sleep scoring method based on single channel electroencephalogram (EEG) is essential not only for alleviating the burden of the clinicians of analyzing a high volume of data but also for making a low-power wearable sleep monitoring system feasible. However, most of the existing works are either multichannel or multiple physiological signal based or yield poor algorithmic performance. In this study, we propound a data-driven and robust automatic sleep staging scheme that uses single channel EEG signal. Decomposing the EEG signal segments using Empirical Mode Decomposition (EMD), we extract various statistical moment based features. The effectiveness of statistical features in the EMD domain is inspected. Statistical analysis is performed for feature selection. We then employ Adaptive Boosting and decision trees to perform classification. The performance of our feature extraction scheme is studied for various choices of classification models. Experimental outcomes manifest that the performance of the proposed sleep staging algorithm is better than that of the state-of-the-art ones. Furthermore, the proposed method's non-REM 1 stage detection accuracy is better than most of the existing works.

Słowa kluczowe

EN

EEG; AdaBoost; ensemble learning; sleep scoring; empirical mode decomposition

PL

EEG; AdaBoost; uczenie zespołowe; empiryczna dekompozycja sygnału

• Wydawca: Nałęcz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences ; Elsevier
• Czasopismo: Biocybernetics and Biomedical Engineering
• Rocznik: 2016
• Tom: Vol. 36, no. 1
• Strony: 248--255
• Opis fizyczny: Bibliogr. 34 poz., tab., wykr.

Twórcy

autor

Hassan A. R.

• Department of Electrical and Electronic Engineering, Bangladesh University of Engineering and Technology, 508/3, South Goran, Dhaka 1219, Bangladesh

autor

Bhuiyan M. I. H.

• Department of Electrical and Electronic Engineering, Bangladesh University of Engineering and Technology, Dhaka 1205, Bangladesh

Bibliografia

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Uwagi

PL

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę.