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.
| Author: | Maksym GaidukORCiD, Ralf SeepoldORCiDGND, Thomas PenzelORCiDGND, Juan Antonio OrtegaORCiD, Martin GlosORCiDGND, Natividad Martínez MadridORCiD |
|---|---|
| DOI: | https://doi.org/10.1109/EMBC.2019.8857596 |
| ISBN: | 978-1-5386-1311-5 |
| 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 |
| Publisher: | IEEE |
| Document Type: | Conference Proceeding |
| Language: | English |
| Year of Publication: | 2019 |
| Release Date: | 2019/09/10 |
| Tag: | Sleep study; Multinomial logistic regression; Sleep/Wake states |
| First Page: | 5712 |
| Last Page: | 5715 |
| Note: | 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): |  Urheberrechtlich geschützt |
