Non-invasive and wearable thermometer for continuous monitoring of core body temperature under various convective conditions

D. Matsunaga, Y. Tanaka, M. Seyama, K. Nagashima

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

We describe the design of a thermometer that can be worn during everyday activities for monitoring core body temperature (CBT) at the skin surface. This sensor estimates the CBT by measuring the heat flux from the body core based on a thermal conductive model. The heat flux is usually affected by the ambient convective conditions (e.g. air conditioner or posture), which in turn affects the model's accuracy. Thus, we analytically investigated heat conduction and designed a sensor interface that would be robust to convection changes. We performed an in vitro experiment and a preliminary in vivo experiment. The accuracy of CBT in an in vitro experiments was 0.1°C for convective values ranging from 0 to 1.2 m/s. The wearable thermometer has high potential as non-invasive CBT monitor.

Original languageEnglish
Title of host publication42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society
Subtitle of host publicationEnabling Innovative Technologies for Global Healthcare, EMBC 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4377-4380
Number of pages4
ISBN (Electronic)9781728119908
DOIs
Publication statusPublished - 2020 Jul
Event42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society, EMBC 2020 - Montreal, Canada
Duration: 2020 Jul 202020 Jul 24

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Volume2020-July
ISSN (Print)1557-170X

Conference

Conference42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society, EMBC 2020
Country/TerritoryCanada
CityMontreal
Period20/7/2020/7/24

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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