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Sensors 2016, 16(3), 409; doi:10.3390/s16030409

Physiological Signal Monitoring Bed for Infants Based on Load-Cell Sensors

1
Interdisciplinary Program in Bioengineering, Graduate School, Seoul National University, Seoul 08826, Korea
2
Department of Biomedical Engineering, College of Medicine, Seoul National University, Seoul 03080, Korea
*
Author to whom correspondence should be addressed.
Academic Editor: Panicos Kyriacou
Received: 29 December 2015 / Revised: 26 February 2016 / Accepted: 15 March 2016 / Published: 19 March 2016
(This article belongs to the Collection Sensors for Globalized Healthy Living and Wellbeing)
View Full-Text   |   Download PDF [5457 KB, uploaded 21 March 2016]   |  

Abstract

Ballistocardiographs (BCGs), which record the mechanical activity of the heart, have been a subject of interest for several years because of their advantages in providing unobtrusive physiological measurements. BCGs could also be useful for monitoring the biological signals of infants without the need for physical confinement. In this study, we describe a physiological signal monitoring bed based on load cells and assess an algorithm to extract the heart rate and breathing rate from the measured load-cell signals. Four infants participated in a total of 13 experiments. As a reference signal, electrocardiogram and respiration signals were simultaneously measured using a commercial device. The proposed automatic algorithm then selected the optimal sensor from which to estimate the heartbeat and respiration information. The results from the load-cell sensor signals were compared with those of the reference signals, and the heartbeat and respiration information were found to have average performance errors of 2.55% and 2.66%, respectively. The experimental results verify the positive feasibility of BCG-based measurements in infants. View Full-Text
Keywords: ballistocardiographs; physiological signal monitoring; infants; load-cell sensor; automatic optimal sensor selection algorithm ballistocardiographs; physiological signal monitoring; infants; load-cell sensor; automatic optimal sensor selection algorithm
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Lee, W.K.; Yoon, H.; Han, C.; Joo, K.M.; Park, K.S. Physiological Signal Monitoring Bed for Infants Based on Load-Cell Sensors. Sensors 2016, 16, 409.

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