Ponencia
Recognition of Sleep/Wake States analyzing Heart Rate, Breathing and Movement Signals
Autor/es | Gaiduk, Maksym
Seepold, Ralf Penzel, Thomas Ortega Ramírez, Juan Antonio Glos, Martin Martínez Madrid, Natividad |
Departamento | Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos |
Fecha de publicación | 2019-07 |
Fecha de depósito | 2023-02-20 |
Publicado en |
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ISBN/ISSN | 978-1-5386-1312-2 (PoD) 978-1-5386-1311-5 (online) 1557-170X (PoD) 1558-4615 (online) |
Resumen | 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 ... 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. |
Cita | Gaiduk, M., Seepold, R., Penzel, T., Ortega Ramírez, J.A., Glos, M. y Martínez Madrid, N. (2019). Recognition of Sleep/Wake States analyzing Heart Rate, Breathing and Movement Signals. En EMBC 2019: 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Berlín (Alemania). |
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