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A method for measuring human body composition using digital images.

Olivia Affuso1,2, Ligaj Pradhan3, Chengcui Zhang3

  • 1Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, United States.

Plos One
|November 6, 2018
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Summary
This summary is machine-generated.

A new computer algorithm using digital photographs can accurately estimate body fat percentage (%BF) in children and adults. This method offers a valid alternative to traditional body mass index (BMI) measurements.

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Area of Science:

  • Biometrics
  • Medical Imaging
  • Anthropometry

Background:

  • Body Mass Index (BMI) is a common but limited proxy for obesity.
  • Estimating body fat (BF) accurately is crucial for health assessments.
  • Trained observers can estimate BF with reasonable accuracy, but objective methods are needed.

Purpose of the Study:

  • To develop and validate a computer algorithm for estimating %BF using digital photographs.
  • To assess the algorithm's accuracy in children and adults compared to dual x-ray absorptiometry (DXA).

Main Methods:

  • A support vector regression (SVR) model was trained using age, sex, race, BMI, and photographic data (body volume and shape).
  • Dual x-ray absorptiometry (DXA) served as the criterion method for %BF measurement.
  • Validation was performed separately for children and adults using digital images.

Main Results:

  • The photographic method (%BFPHOTO) showed strong correlations with DXA-measured %BF (r=0.80 in children, r=0.87 in adults).
  • These correlations were statistically higher than those obtained using BMI alone (%BFNOPHOTO).
  • The algorithm provided valid %BF estimates in both pediatric and adult populations.

Conclusions:

  • A novel photographic method provides valid body fat percentage estimates in children and adults.
  • This digital image-based approach offers a promising tool for obesity assessment.
  • Future research should focus on developing norms for diverse demographic subgroups.