Predicting Metabolic Cost of Running with and without Backpack Loads,

Abstract

A mathematical equation to predict the metabolic cost of standing or walking (Mw) has been developed. It is, however limited to speeds < 2.2 m/s and overestimated the metabolic cost of walking or running at higher speeds. This study's purpose was to develop a mathematical model for the metabolic cost of running (Mr)in order to predict the metabolic cost under a wide range of speeds, external loads and grades. Twelve male subjects were tested on a level treadmill under different combinations of speed and external load. Speed varied between 2.2 to 3.2 m/s using 0.2 m/s intervals and external loads between 0.30 kg with 10 kg intervals. Four of the subjects were also tested at 2 and 4% incline while speed and load remained constant (2.4 m/s, 20 kg). The model developed is based on Mw and is proportionately linear with external load (L) carried as follows: Mr = Mw - 0.5 (1-0.01L) (Mw-15L-850) -- in water. The correlation coefficient between predicted and observed values was 0.99 (P<0.01) with SER of 7.7%. The accuracy of the model was validated by its ability to predict the metabolic cost of running under different conditions extracted from the literature. A highly significant correlation (r = 0.95, P<0.02, SER = 6.5%) was found between our predicted and the reported values. Keywords: Work efficiency, Load carriage, Backpack load, Mathematical prediction, Ergonomics.

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Document Details

Document Type
Technical Report
Publication Date
Oct 23, 1986
Accession Number
ADA174858

Entities

People

  • K. B. Pandolf
  • L. A . Stroschein
  • Y. Epstein

Organizations

  • United States Army Research Institute of Environmental Medicine

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Accuracy
  • Air Resistance
  • Backpacks
  • Body Weight
  • Carriages
  • Center Of Gravity
  • Classification
  • Clothing
  • Coefficients
  • Databases
  • Environment
  • Heart Rate
  • Mathematical Models
  • Measurement
  • Military Research
  • Regression Analysis
  • Security

Readers

  • Computational Modeling and Simulation
  • Exercise and Sports Science.
  • Regression Analysis.