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Evaluating Body Movement and Breathing Signals for Identification of Sleep/Wake States

  • Recognition of sleep and wake states is one of the relevant parts of sleep analysis. Performing this measurement in a contactless way increases comfort for the users. We present an approach evaluating only movement and respiratory signals to achieve recognition, which can be measured non-obtrusively. The algorithm is based on multinomial logistic regression and analyses features extracted out of mentioned above signals. These features were identified and developed after performing fundamental research on characteristics of vital signals during sleep. The achieved accuracy of 87% with the Cohen’s kappa of 0.40 demonstrates the appropriateness of a chosen method and encourages continuing research on this topic.

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Metadaten
Author:Maksym GaidukORCiD, Ralf SeepoldORCiDGND, Natividad Martínez MadridORCiD, Thomas PenzelORCiDGND, Lucas Weber, Massimo ContiORCiD, Simone OrcioniORCiD, Juan Antonio OrtegaORCiD
DOI:https://doi.org/10.1007/978-3-030-95498-7_29
ISBN:978-3-030-95498-7
ISBN:978-3-030-95497-0
Parent Title (English):Applications in Electronics Pervading Industry, Environment and Society : ApplePies 2021, 21.-22. September 2021, Pisa, Italy, (Lecture Notes in Electrical Engineering ; Vol. 866)
Publisher:Springer
Place of publication:Cham
Document Type:Conference Proceeding
Language:English
Year of Publication:2022
Release Date:2022/06/02
Tag:Sleep medicine; Breathing; Movement signals
First Page:206
Last Page:211
Institutes:Institut für Angewandte Forschung - IAF
Relevance:Keine peer reviewed Publikation (Wissenschaftlicher Artikel und Aufsatz, Proceeding, Artikel in Tagungsband)
Open Access?:Nein
Licence (English):License LogoLizenzbedingungen Springer