English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

With increasing heat-wave frequency, the prevention and public awareness of heat-related illnesses has become an essential topic. In the standard for heat strain and stress, empirical guidelines to prevent excess core temperature rise above 1 &#x00B0;C have been prescribed for workers. However, measuring core temperature change in our daily life or working place is not straightforward. The estimation of core temperature from measured vital signals in a non-invasive manner is thus essential for the management of heat stress or strain. Here, we propose an estimation method for core temperature change by a simplified thermodynamics model with the measured heart rate and ambient conditions (temperature and relative humidity). Our proposed model is based on a two-layer two-compartment model with tuned parameters, which were derived from comparison between the computations using high-resolution anatomical human body model. Our model exhibited good agreement with the measured core temperature rise; the computed and measured core temperature rise for the naked trial were 0.54 &#x00B0;C and 0.53 &#x00B0;C, whereas those for the clothed trial were 0.70 &#x00B0;C, and 0.71 &#x00B0;C, respectively. Furthermore, our compartment model with vital data measured from a wearable device achieved good estimation in real time for field measurement in addition to computational replication with a previous study.

Body Core Temperature Estimation Using New Compartment Model With Vital Data From Wearable Devices