TY  - CHAP
U1  - Konferenzveröffentlichung
A1  - Rätzer, Sebastian
A1  - Gaiduk, Maksym
A1  - Seepold, Ralf
T1  - Heart Rate Detection Using a Non-obtrusive Ballistocardiography Signal
T2  - Intelligent Decision Technologies : Proceedings of the 14th KES-IDT 2022 Conference (Smart Innovation, Systems and Technologies SIST, Vol. 309)
N2  - Sleep is an important part of our life that significantly influences our health and well-being. The monitoring of sleep can provide data based on which sleep quality could be improved. This paper presents a system for heart rate detection during sleep. The data is collected from sensors underneath the test subjects. Though the data contains noise, it needs to be filtered to remove it. Due to the low strength of the signals, they need to be amplified after filtering. At some points of the signal, particular heartbeats may not be tracked by sensors due to the failure of a sensor or other reasons, which should be considered. The heart rate is detected in intervals of 15 s. A tool is implemented that detects the heart rate and visualizes it. The preprocessing of the data is performed with several filters: a highpass filter, a band-reject filter, a lowpass filter, and a motion detector. After the preprocessing of the data, the quality of the signal is significantly increased, and detection is possible.
KW  - Ballistocardiography (BCG)
KW  - Short time Fourier transformation (STFT)
KW  - Empirical mode decomposition (EMD)
KW  - Sleep study
Y1  - 2022
U6  - https://doi.org/10.1007/978-981-19-3444-5_35
DO  - https://doi.org/10.1007/978-981-19-3444-5_35
SP  - 405
EP  - 416
PB  - Springer
CY  - Singapore
ER  -