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

  • This document presents an algorithm for a nonobtrusive 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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Metadaten
Author of HS ReutlingenMartínez Madrid, Natividad
DOI:https://doi.org/https://doi.org/10.1109/EMBC.2019.8857596
Erschienen in:Biomedical engineering ranging from wellness to intensive care : 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC): July 23-27, Berlin
Publisher:IEEE
Place of publication:Piscataway, NJ
Document Type:Conference proceeding
Language:English
Publication year:2019
Page Number:4
First Page:5712
Last Page:5715
DDC classes:004 Informatik
Open access?:Nein
Licence (German):License Logo  In Copyright - Urheberrechtlich geschützt