Identifying an appropriate area to facilitate the cardiorespiratory measurement during sleep monitoring
- Measuring cardiorespiratory parameters in sleep, using non-contact sensors and the Ballistocardiography technique has received much attention due to the low-cost, unobtrusive, and non-invasive method. Designing a user-friendly, simple-to-use, and easy-to-deployment preserving less error-prone remains open and challenging due to the complex morphology of the signal. In this work, using four forcesensitive resistor sensors, we conducted a study by designing four distributions of sensors, in order to simplify the complexity of the system by identifying the region of interest for heartbeat and respiration measurement. The sensors are deployed under the mattress and attached to the bed frame without any interference with the subjects. The four distributions are combined in two linear horizontal, one linear vertical, and one square, covering the influencing region in cardiorespiratory activities. We recruited 4 subjects and acquired data in four regular sleeping positions, each for a duration of 80 seconds. The signal processing was performed using discrete wavelet transform bior 3.9 and smooth level of 4 as well as bandpass filtering. The results indicate that we have achieved the mean absolute error of 2.35 and 4.34 for respiration and heartbeat, respectively. The results recommend the efficiency of a triangleshaped structure of three sensors for measuring heartbeat and respiration parameters in all four regular sleeping positions.
Author of HS Reutlingen | Martínez Madrid, Natividad |
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DOI: | https://doi.org/10.1109/EMBC40787.2023.10341186 |
ISBN: | 979-8-3503-2447-1 |
ISSN: | 2694-0604 |
Erschienen in: | 2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), proceedings, Sydney, Australia, 24th - 27th July 2023 |
Publisher: | IEEE |
Place of publication: | Piscataway |
Document Type: | Conference proceeding |
Language: | English |
Publication year: | 2023 |
Tag: | heart beat; position measurement; sensor systems; signal processing; sleep apnea; thorax; transforms |
Page Number: | 6 |
DDC classes: | 610 Medizin, Gesundheit |
Open access?: | Nein |
Licence (German): | ![]() |