Body shape and performance on the US Army Combat Fitness Test: Insights from a 3D body image scanner

Mobile phone applications for 3-dimensional scanning and digital anthropometry: a precision comparison with traditional scanners

BACKGROUND

The precision of digital anthropometry through 3-dimensional (3D) scanning has been established for relatively large, expensive, non-portable systems. The comparative performance of modern mobile applications is unclear.

SUBJECTS/METHODS

Forty-six adults (age: 23.3 ± 5.3 y; BMI: 24.4 ± 4.1 kg/m2) were assessed in duplicate using: (1) a mobile phone application capturing two individual 2D images, (2) a mobile phone application capturing serial images collected during a subject's complete rotation, (3) a traditional scanner with a time of flight infrared sensor collecting visual data from a subject being rotated on a mechanical turntable, and (4) a commercial measuring booth with structured light technology using 20 infrared depth sensors positioned in the booth. The absolute and relative technical error of measurement (TEM) and intraclass correlation coefficient (ICC) for each method were established.

RESULTS

Averaged across circumferences, the absolute TEM, relative TEM, and ICC were (1) 0.9 cm, 1.5%, and 0.975; (2) 0.5 cm, 0.9%, and 0.986; (3) 0.8 cm, 1.5%, and 0.974; and (4) 0.6 cm, 1.1%, and 0.985. For total body volume, these values were (1) 2.2 L, 3.0%, and 0.978; (2) 0.8 L, 1.1%, and 0.997; (3) 0.7 L, 0.9%, and 0.998; and (4) 0.8 L, 1.1%, and 0.996, with segmental volumes demonstrating higher relative errors.

CONCLUSION

A 3D scanning mobile phone application involving full rotation of subjects in front of a smartphone camera exhibited similar reliability to larger, less portable, more expensive 3D scanners. In contrast, larger errors were observed for a mobile scanning application utilizing two 2D images, although the technical errors were acceptable for some applications.

Raising the U.S. Army Height-Weight (Body Mass Index) Standards: Quantifying Metabolic Risk

BACKGROUND & OBJECTIVES

The U.S. Army fell 25% short of its recruitment goal in 2022 and therefore, increasing the eligibility pool for potential recruits is of interest. Raising the body mass index (BMI) standards for eligibility presents a path to increase the recruitable population; however, there may be additional costs incurred due to attendant health risks that may be present in individuals with higher BMI.

METHODS

We filtered the 2017-2020 National Health and Nutrition Examination Survey by age (17-25 years) and BMI (up to 30 kg/m2). A k-means cluster analysis was performed on the filtered dataset for the variables used to determine metabolic syndrome. Metabolic syndrome Clusters were characterized through summary statistics and compared over clinical measurements and questionnaire responses.

RESULTS

Five distinct clusters were identified and mean BMI in two clusters (Clusters1 and 3) exceeded the current U.S. Army BMI thresholds. Of these two clusters, Cluster 1 members had metabolic syndrome. Cluster 3 members were at higher risk for metabolic syndrome compared to members of Clusters 2, 4, and 5. Mean waist circumference was slightly lower in Cluster 3 compared to Cluster 1. None of the clusters had significant differences in depression scores, poverty index, or frequency of dental visits.

CONCLUSIONS

Potential recruits from Cluster 1 have excessive health risk and may incur substantial cost to the U.S. Army if enlisted. However, potential recruits from Cluster 3 appear to add little risk and offer an opportunity to increase the pool for recruiting.