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

• Published in: Sensors (Basel, Switzerland) Vol. 16; no. 3; p. 409
• Main Authors: Lee, Won, Yoon, Heenam, Han, Chungmin, Joo, Kwang, Park, Kwang
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI 19.03.2016; MDPI AG
• Subjects: automatic optimal sensor selection algorithm; ballistocardiographs; Ballistocardiography - methods; Electrocardiography - instrumentation; Heart Rate - physiology; Humans; Infant; infants; load-cell sensor; Monitoring, Physiologic - methods; physiological signal monitoring; Respiratory Rate - physiology; Signal Processing, Computer-Assisted; automatic optimal sensor selection algorithm; ballistocardiographs; infants; physiological signal monitoring; load-cell sensor
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s16030409

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.