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A new 2-regression model for the Actical accelerometer.

S E Crouter1, D R Bassett

  • 1Division of Nutritional Sciences, Cornell University, Ithaca, NY,USA. Scott.crouter@umb.edu

British Journal of Sports Medicine
|September 1, 2007
PubMed
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A new 2-regression model accurately estimates physical activity energy expenditure (METs) using Actical accelerometer data. This model improves upon existing equations for various activities, enhancing physical activity research.

Area of Science:

  • Exercise Physiology
  • Biomedical Engineering
  • Physical Activity Measurement

Background:

  • Accurate measurement of physical activity energy expenditure is crucial for health research.
  • Existing accelerometer-based equations for estimating METs have limitations.
  • The Actical accelerometer is widely used, necessitating refined predictive models.

Purpose of the Study:

  • To develop and validate a novel 2-regression model for estimating METs from Actical accelerometer activity counts.
  • To compare the accuracy of the new model against existing equations.

Main Methods:

  • Developed a 2-regression model using Actical accelerometer data and measured oxygen consumption from 48 participants across 18 activities.
  • Utilized coefficient of variation (CV) of activity counts to select appropriate regression equations (exponential for CV ≤13%, cubic for CV >13%).

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  • Cross-validated the model with 15 independent tests and compared it to existing equations.

    • Main Results:

    • The new model demonstrated strong predictive power with R(2) values of 0.912 (exponential) and 0.884 (cubic).
    • Cross-validation showed the model's estimates were within 0.56 METs of measured values for most activities (p≥0.05), except cycling.
    • The model showed improved accuracy compared to existing equations for the Actical accelerometer.

    Conclusions:

    • The developed 2-regression model provides a more accurate estimation of METs for a wide range of physical activities compared to current methods.
    • This refined model can enhance the precision of physical activity energy expenditure assessments in research.
    • Further validation may be needed for specific activities like cycling.