A review of automated sleep stage scoring based on physiological signals for the new millennia

FAUST, Oliver, RAZAGHI, H., BARIKA, R., CIACCIO, E.J. and ACHARYA, U.R. (2019). A review of automated sleep stage scoring based on physiological signals for the new millennia. Computer Methods and Programs in Biomedicine, 176, 81-91.

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Official URL: https://www.sciencedirect.com/science/article/pii/...
Link to published version:: https://doi.org/10.1016/j.cmpb.2019.04.032

Abstract

Background and Objective: Sleep is an important part of our life. That importance is highlighted by the multitude of health problems which result from sleep disorders. Detecting these sleep disorders requires an accurate interpretation of physiological signals. Prerequisite for this interpretation is an understanding of the way in which sleep stage changes manifest themselves in the signal waveform. With that understanding it is possible to build automated sleep stage scoring systems. Apart from their practical relevance for automating sleep disorder diagnosis, these systems provide a good indication of the amount of sleep stage related information communicated by a specific physiological signal. Methods: This article provides a comprehensive review of automated sleep stage scoring systems, which were created since the year 2000. The systems were developed for Electrocardiogram (ECG), Electroencephalogram (EEG), Electrooculogram (EOG), and a combination of signals. Results: Our review shows that all of these signals contain information for sleep stage scoring. Conclusions: The result is important, because it allows us to shift our research focus away from information extraction methods to systemic improvements, such as patient comfort, redundancy, safety and cost.

Item Type: Article
Uncontrolled Keywords: 0903 Biomedical Engineering; Medical Informatics
Identification Number: https://doi.org/10.1016/j.cmpb.2019.04.032
Page Range: 81-91
SWORD Depositor: Symplectic Elements
Depositing User: Symplectic Elements
Date Deposited: 29 May 2019 11:32
Last Modified: 26 Jun 2019 09:45
URI: http://shura.shu.ac.uk/id/eprint/24637

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