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Author Spotlight: Advancements in 3D Optical Imaging for Comprehensive Body Composition Assessment in Modern Research
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Validation of a three-dimensional body scanner for body composition measures
Michelle M Harbin1, Alexander Kasak2, Joseph D Ostrem3
1Laboratory of Integrative Human Physiology, School of Kinesiology, University of Minnesota, Minneapolis, MN, 55455, USA. harb0085@umn.edu.
European Journal of Clinical Nutrition
|December 31, 2017
Summary
An infrared 3D body scanner underestimated body fat percentage compared to traditional methods like hydrostatic weighing. Its accuracy decreases with higher adiposity, requiring algorithm adjustments for reliable body composition analysis.
Area of Science:
- Anthropometry
- Body Composition Analysis
- Biotechnology
Background:
- Accurate body composition assessment is crucial for health and fitness evaluations.
- Traditional methods like hydrostatic weighing (HW) and bioelectrical impedance analysis (BIA) have limitations.
- Emerging technologies like 3D scanning offer potential for non-invasive body composition measurement.
Purpose of the Study:
- To evaluate the accuracy of an infrared 3D body scanner for determining body fat percent (BF%) in adults.
- To compare the 3D scanner's BF% measurements against established methods: HW, BIA, skinfolds, and girths.
- To identify potential discrepancies and limitations of the 3D scanning technology in body composition analysis.
Main Methods:
- A study involving 265 adults (119 males) with diverse body mass index (BMI) values.
- BF% was measured using an infrared 3D body scanner, HW, BIA, skinfolds, and girth measurements.
- Statistical analysis included repeated measures ANOVA and multivariate ANOVA to compare methods and assess effects of sex and method.
Main Results:
- Significant differences in BF% were found among all measurement methods (p < 0.001).
- The 3D scanner yielded significantly lower BF% (18.1%) compared to HW (22.8%), BIA (20.1%), skinfolds (19.7%), and girths (21.2%).
- 3D scanner precision diminished with increasing adiposity, suggesting algorithmic inconsistencies.
Conclusions:
- The infrared 3D body scanner currently underestimates BF% when compared to established methods.
- The technology's accuracy is compromised at higher levels of adiposity.
- A correction factor within the 3D scanner's algorithm is necessary to improve its validity for body composition assessment.
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