TY  - CHAP
U1  - Konferenzveröffentlichung
A1  - Weber, Lucas
A1  - Gaiduk, Maksym
A1  - Seepold, Ralf
A1  - Martínez Madrid, Natividad
A1  - Glos, Martin
A1  - Penzel, Thomas
T1  - Enhancing current cardiorespiratory-based approaches of sleep stage classification by temporal feature stacking
T2  - 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 1-5 November 2021, Mexico, proceedings
N2  - This paper presents a generic method to enhance performance and incorporate temporal information for cardiorespiratory-based sleep stage classification with a limited feature set and limited data. The classification algorithm relies on random forests and a feature set extracted from long-time home monitoring for sleep analysis. Employing temporal feature stacking, the system could be significantly improved in terms of Cohen’s κ and accuracy. The detection performance could be improved for three classes of sleep stages (Wake, REM, Non-REM sleep), four classes (Wake, Non-REM-Light sleep, Non-REM Deep sleep, REM sleep), and five classes (Wake, N1, N2, N3/4, REM sleep) from a κ of 0.44 to 0.58, 0.33 to 0.51, and 0.28 to 0.44 respectively by stacking features before and after the epoch to be classified. Further analysis was done for the optimal length and combination method for this stacking approach. Overall, three methods and a variable duration between 30 s and 30 min have been analyzed. Overnight recordings of 36 healthy subjects from the Interdisciplinary Center for Sleep Medicine at Charité-Universitätsmedizin Berlin and Leave-One-Out-Cross-Validation on a patient-level have been used to validate the method.
KW  - measurement
KW  - stacking
KW  - training data
KW  - feature extraction
KW  - biology
KW  - classification algorithms
KW  - rapid eye movement sleep
Y1  - 2021
SN  - 2694-0604
SS  - 2694-0604
SN  - 978-1-7281-1179-7
SB  - 978-1-7281-1179-7
U6  - https://doi.org/10.1109/EMBC46164.2021.9630743
DO  - https://doi.org/10.1109/EMBC46164.2021.9630743
SP  - 5518
EP  - 5522
S1  - 5
PB  - IEEE
CY  - Piscataway, NJ
ER  -