@inproceedings{6bc8a0d028a54799b18ae6bf63d2d0db,
title = "Position on the use of low-cost sensors for non-intrustive newborn sepsis monitoring",
abstract = "Neonatal sepsis is a major health problem in the neonatal intensive care unit (NICU). We have developed an non-intrusive system to measure heart rate (HR) information based on BCG sensors embedded in the clothes of the newborn. We utilize multiple statistical metrics of heart rate characteristics (HRC) including RR intervals and of standard deviation of HR, sample asymmetry and sample entropy, to build a warning system for sepsis monitoring. Our system achieves a specificity rate close to 99% and a recall rate around 92% is currently operational at an university hospital.",
author = "Paweeya Raknim and Lan, {Kun Chan} and Linker, {Yung Chieh} and Lu, {Yen Tzu}",
year = "2019",
month = jun,
day = "12",
doi = "10.1145/3325424.3329670",
language = "English",
series = "WearSys 2019 - Proceedings of the 5th ACM Workshop on Wearable Systems and Applications, co-located with MobiSys 2019",
publisher = "Association for Computing Machinery, Inc",
pages = "39--40",
booktitle = "WearSys 2019 - Proceedings of the 5th ACM Workshop on Wearable Systems and Applications, co-located with MobiSys 2019",
note = "5th ACM Workshop on Wearable Systems and Applications, WearSys 2019, co-located with MobiSys 2019 ; Conference date: 21-06-2019",
}