Accuracy and reliability of a low-cost, handheld 3D imaging system for child anthropometry

Joel Conkle1, Parminder S Suchdev1,2,3,4, Eugene Alexander5

  • 1Nutrition and Health Sciences Program, Laney Graduate School, Emory University, Atlanta, GA, United States of America.

Plos One
|October 26, 2018
PubMed

Insights

A new 3D imaging system shows reliable results for measuring child stature, head circumference, and arm circumference, offering a promising tool for childhood malnutrition assessment.

Area of Science:

  • Anthropometry and Child Health
  • Medical Imaging Technology
  • Public Health and Nutrition

Background:

  • Traditional anthropometry for childhood malnutrition is limited by measurement quality.
  • There is a need for improved, reliable measurement approaches.
  • 3D imaging technology presents a potential alternative for accurate child measurements.

Purpose of the Study:

  • To evaluate a 3D imaging system's ability to accurately measure child stature, head circumference, and arm circumference.
  • To compare the reliability and accuracy of 3D scan-derived measurements against traditional manual measurements.

Main Methods:

  • Recruited 474 children aged 0-5 years in metro Atlanta, Georgia.
  • Utilized a 3D imaging system and manual measurements taken by two anthropometrists.
  • Assessed measurement reliability of repeated 3D scans against manual measurements.

Main Results:

  • 3D imaging system demonstrated high reliability, with repeated scans within 1 mm of manual measurements for stature, head circumference, and arm circumference.
  • Systematic bias was observed: 3D imaging overestimated stature by 6 mm and head circumference by 3 mm, and underestimated arm circumference by 2 mm.
  • The 3D imaging system is reliable, low-cost, portable, and motion-tolerant.

Conclusions:

  • The 3D imaging system is a reliable tool for child anthropometry, suitable for routine nutritional assessment.
  • Further research on accuracy and software development is necessary before clinical recommendations.
  • 3D imaging holds potential to improve childhood malnutrition assessment.

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