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An E-Textile Respiration Sensing System for NICU Monitoring: Design and Validation

Authors :
Gozde Cay
Kunal Mankodiya
Manob Jyoti Saikia
Amy L. Salisbury
Yalda Shahriari
Laurie Hoffman
Krishna Venkatasubramanian
James F. Padbury
Vignesh Ravichandran
Anna Gitelson-Kahn
Abbot R. Laptook
Source :
Journal of Signal Processing Systems
Publication Year :
2021
Publisher :
Springer US, 2021.

Abstract

The world is witnessing a rising number of preterm infants who are at significant risk of medical conditions. These infants require continuous care in Neonatal Intensive Care Units (NICU). Medical parameters are continuously monitored in premature infants in the NICU using a set of wired, sticky electrodes attached to the body. Medical adhesives used on the electrodes can be harmful to the baby, causing skin injuries, discomfort, and irritation. In addition, respiration rate (RR) monitoring in the NICU faces challenges of accuracy and clinical quality because RR is extracted from electrocardiogram (ECG). This research paper presents a design and validation of a smart textile pressure sensor system that addresses the existing challenges of medical monitoring in NICU. We designed two e-textile, piezoresistive pressure sensors made of Velostat for noninvasive RR monitoring; one was hand-stitched on a mattress topper material, and the other was embroidered on a denim fabric using an industrial embroidery machine. We developed a data acquisition system for validation experiments conducted on a high-fidelity, programmable NICU baby mannequin. We designed a signal processing pipeline to convert raw time-series signals into parameters including RR, rise and fall time, and comparison metrics. The results of the experiments showed that the relative accuracies of hand-stitched sensors were 98.68 (top sensor) and 98.07 (bottom sensor), while the accuracies of embroidered sensors were 99.37 (left sensor) and 99.39 (right sensor) for the 60 BrPM test case. The presented prototype system shows promising results and demands more research on textile design, human factors, and human experimentation.

Details

Language :
English
ISSN :
19398115 and 19398018
Database :
OpenAIRE
Journal :
Journal of Signal Processing Systems
Accession number :
edsair.doi.dedup.....c828a191f1b29c1671f4e47235f4b363