An Evaluation of Localized Sweating Rates for Predicting Total Body Sweating Rates.

Abstract

This project accessed the accuracy of estimating whole body sweating rates (WBSR) from local sweating rates (LSR) measured with sweat collection capsules containing filter paper. Sweat was collected in capsules strapped on five locations of the body: (1) midforehead, (2) superiorflexor side of the right forearm, (3) left pectoralis major, (4) medial midsection of the left thigh, and (5) upper medial side of the left calf. Sweating rates of 10 male subjects were measured while they rested at an air temperature of 39.4 C and 58.4% RH, and while they ran on a treadmill at a work output of 60% VO2 max with an air temperature of 35.5 C and 33.2% RH. Among all subjects the WBSR averaged 4.3147 g/min sq m during rest and 7.6062 g/min sq m during exercise. The LSR from any one of the five locations was a poor predictor of WBSR. Multiple regression equations which included LSRs from all five locations gave an r squared > 90 for 5 subjects during rest and exercise. The multiple regression equations derived from the data combined from all subjects was not as good a predictor of WBSR as some of the equations derived for individual subjects, i.e., r squared = 70.3 for data during rest and r squared = 46.1 for data during exercise. Four equations which weighted the LSRs with the corresponding skin area factors provide a poor estimate of WBSR (r squared = 53.9). (Author)

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1981
Accession Number
ADA111902

Entities

People

  • James A. Gessaman

Organizations

  • Utah State University

Tags

Communities of Interest

  • Space

DTIC Thesaurus Topics

  • Abstracts
  • Accuracy
  • Air Temperature
  • Boundaries
  • Coefficients
  • Data Analysis
  • Environment
  • Equations
  • Filter Paper
  • Forehead
  • Intervals
  • Linear Regression Analysis
  • Measurement
  • Regression Analysis
  • Rubber Gaskets
  • Time Intervals
  • Treadmills

Readers

  • Exercise and Sports Science.
  • Geochemistry
  • Regression Analysis.