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Predicting ambulatory energy expenditure in lower limb amputees using multi-sensor methods.

Peter Ladlow1,2, Tom E Nightingale1, M Polly McGuigan1

  • 1Department for Health, University of Bath, Bath, United Kingdom.

Plos One
|February 1, 2019
PubMed
Summary

A new algorithm combining accelerometry and heart rate data (GT3X+HR) accurately estimates physical activity energy expenditure (PAEE) in individuals with lower-limb amputation. This method is more valid than the Actiheart (AHR) device, offering a better tool for assessing PAEE in this population.

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Area of Science:

  • Biomedical Engineering
  • Exercise Physiology
  • Rehabilitation Science

Background:

  • Accurate assessment of physical activity energy expenditure (PAEE) is crucial for managing health in individuals with lower-limb amputation.
  • Existing methods for PAEE estimation may have limitations in this specific population.

Purpose of the Study:

  • To validate a derived algorithm (GT3X+HR) using tri-axial accelerometry and heart rate (HR) data for estimating PAEE.
  • To compare the validity of the GT3X+HR algorithm against a research-grade device (Actiheart - AHR) in individuals with traumatic lower-limb amputation.

Main Methods:

  • Twenty-eight participants (unilateral/bilateral lower-limb amputation, controls) performed standardized activities on a treadmill.
  • PAEE was measured using indirect calorimetry (criterion).
  • An Actigraph GT3X+ accelerometer and HR monitor were used to derive the GT3X+HR algorithm; an Actiheart (AHR) device was also used for comparison.

Main Results:

  • Both GT3X+HR and AHR showed significant relationships with criterion PAEE (P<0.01).
  • The GT3X+HR algorithm demonstrated superior validity, with stronger associations (r=0.91-0.93) and significantly lower percentage errors (15-18%) across all groups compared to AHR (r=0.67-0.86, errors=34-45%).
  • GT3X+HR exhibited the smallest limits of agreement and least error.

Conclusions:

  • Statistically derived algorithms (GT3X+HR) offer a more valid estimation of PAEE in individuals with lower-limb amputation.
  • The proprietary AHR algorithm showed considerable random error in this population, suggesting it is less suitable for PAEE estimation in individuals with lower-limb amputation.