Home
Resource
Modeling individualized thermoregulatory responses to clothing and activity, in hot and cold environments
PDF
PDF format is widely accepted and good for printing.
Plug-in required
PDF-1(4.77 MB)
Citation & Export
View Usage Statistics
Staff View

Citation & Export
Hide

Simple citation

Potter, Adam W.. Modeling individualized thermoregulatory responses to clothing and activity, in hot and cold environments. Retrieved from https://doi.org/doi:10.7282/t3-m9xe-1g83

Export

Click here for information about Citation Management Tools at Rutgers.

Statistics
Hide

Description

TitleModeling individualized thermoregulatory responses to clothing and activity, in hot and cold environments
NamePotter, Adam W. (author); Srinivasan, Shankar (chair); Gohel, Suril (internal member); Looney, David P (outside member); Xu, Xiaojiang (outside member); Santee, William R (outside member); Rutgers University; School of Health Professions
Date Created2019
Other Date2019-08 (degree)
SubjectBiomedical Informatics, Physiology, Body temperature, Soldiers -- Health risk assessment
Extent1 online resource (106 pages) : illustrations
DescriptionThe US military operate in complex and harsh environments with regular risks of succumbing to heat- or cold-related injuries that could have both negative mission and individual health consequences. Objective and Methods: This effort collects human rest and exercise-based research data to compare and validate methods and mixed modeling approaches to provide a clear outline of predictive methods for determining physiological responses to hot and cold exposure (e.g., rise or fall in skin and core body temperatures) based on individual, environment, clothing, and activity. Data: This study collects human and non-human (clothing biophysics) data. Human research data used is from individuals during rest and exercise exposed to hot and cold environments (n = 51); while clothing data is a full range of clothing tested on sweating thermal manikins for measures of thermal and evaporative resistance (n = 93). From this combined data, the goal is test equations or methods for predicting general risk of heat- and cold- related injuries based on individual inputs. Two assessments are conducted, one to assess heat stress predictions (rise of core body temperature) and a second for assessing cold stress predictions (skin temperature fall). Conclusions: Analyses in the heat stress assessment showed empirical methods are capable of predicting within acceptable accuracy rise in core body temperature from group mean data; while individual-based predictions have been shown to be accurate to within an acceptable bias of ± 0.27°C for both in hot and humid environments laboratory (-0.10 ± 0.36) and field conditions (0.23 ± 0.32). Both rational and empirical methods were shown to acceptably predict skin temperatures to within the observed standard deviation (23.14 ± 9.35) (bias, -0.77 ± 3.69°C; MAE, 2.22 ± 3.05°C; and RMSE, 1.49 ± 3.05°C).
NotePh.D.
NoteIncludes bibliographical references
Genretheses, ETD doctoral
Persistent URLhttps://doi.org/doi:10.7282/t3-m9xe-1g83
LanguageEnglish
CollectionSchool of Health Professions ETD Collection
Organization NameRutgers, The State University of New Jersey
RightsThe author owns the copyright to this work.
Version 8.5.5
Rutgers University Libraries - Copyright ©2024