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Recognition of sleep/wake states analyzing heart rate, breathing and movement signals

  • This document presents an algorithm for a non-obtrusive recognition of Sleep/Wake states using signals derived from ECG, respiration, and body movement captured while lying in a bed. As a core mathematical base of system data analytics, multinomial logistic regression techniques were chosen. Derived parameters of the three signals are used as the input for the proposed method. The overall achieved accuracy rate is 84% for Wake/Sleep stages, with Cohen’s kappa value 0.46. The presented algorithm should support experts in analyzing sleep quality in more detail. The results confirm the potential of this method and disclose several ways for its improvement.

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Author:Maksym GaidukORCiD, Ralf SeepoldORCiDGND, Thomas PenzelORCiDGND, Juan Antonio OrtegaORCiD, Martin GlosORCiDGND, Natividad Martínez MadridORCiD
Parent Title (English):41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2019), 23-27 July 2019, Messe Berlin, Germany
Document Type:Conference Proceeding
Year of Publication:2019
Release Date:2019/09/10
Tag:Sleep study; Multinomial logistic regression; Sleep/Wake states
First Page:5712
Last Page:5715
Volltextzugriff für Angehörige der Hochschule Konstanz via IEEE Xplore möglich
Institutes:Fakultät Informatik
Relevance:Keine peer reviewed Publikation (Wissenschaftlicher Artikel und Aufsatz, Proceeding, Artikel in Tagungsband)
Open Access?:Nein
Licence (German):License LogoUrheberrechtlich geschützt