TY  - CHAP
U1  - Konferenzveröffentlichung
A1  - Gaiduk, Maksym
A1  - Seepold, Ralf
A1  - Penzel, Thomas
A1  - Ortega Ramírez, Juan Antonio
A1  - Glos, Martin
A1  - Martínez Madrid, Natividad
T1  - Recognition of sleep/wake states analyzing heart rate, breathing and movement signals
T2  - 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
N2  - 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.
Y1  - 2019
U6  - https://doi.org/https://doi.org/10.1109/EMBC.2019.8857596
DO  - https://doi.org/https://doi.org/10.1109/EMBC.2019.8857596
SP  - 5712
EP  - 5715
S1  - 4
PB  - IEEE
CY  - Piscataway, NJ
ER  -