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Predicting Energy Expenditure During Gradient Walking With a Foot Monitoring Device: Model-Based Approach.

Soon Ho Kim1, Jong Won Kim2, Jung-Jun Park3

  • 1Department of Physics and Astronomy and Center for Theoretical Physics, Seoul National University, Seoul, Republic of Korea.

JMIR Mhealth and Uhealth
|October 25, 2019
PubMed
Summary

This study developed an accurate model for predicting energy expenditure during walking on various slopes. The model, designed for use with a simple wearable device, offers practical insights into calorie consumption.

Keywords:
energy expenditurehuman walkingmHealthphysical activitywearable devices

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Area of Science:

  • Biomechanics
  • Human Physiology
  • Wearable Technology

Background:

  • Commercial devices for measuring energy expenditure often lack accuracy.
  • Accurate energy expenditure tracking is crucial for health and fitness applications.

Purpose of the Study:

  • To develop a predictive model for energy consumption during walking on sloped surfaces.
  • To integrate this model with a simple, wearable device for practical application.

Main Methods:

  • Constructed a mechanics-based model for energy consumption during gradient walking.
  • Developed a foot monitoring system utilizing pressure sensors in shoe insoles.
  • Validated the model using indirect calorimetry during treadmill walking experiments.

Main Results:

  • The model accurately predicted energy consumption across various slopes.
  • For walking at 1.5 m/s, predicted rates were 5.54 kcal/min for average women and 6.89 kcal/min for average men.
  • Achieved a root-mean-square deviation of 0.96 kcal/min and a median percent error of 12.4%.

Conclusions:

  • The developed model accurately predicts energy expenditure during walking on diverse slopes.
  • The model's simplicity, using few variables, makes it suitable for convenient wearable devices.