Title
Automated anthropometric phenotyping with novel Kinect-based three-dimensional imaging method: Comparison with a reference laser imaging system
Document Type
Article
Publication Date
4-1-2016
Abstract
Background/Objectives:Anthropometry for measuring body composition, shape, surface area and volume is important for human clinical research and practice. Although training and technical skills are required for traditional tape and caliper anthropometry, a new opportunity exists for automated measurement using newly developed relatively low-cost three-dimensional (3D) imaging devices. The aim of this study was to compare results provided by a Kinect-based device to a traditional laser 3D reference system.Subjects/Methods:Measurements made by the evaluated device, a hybrid of commercially purchased hardware (KX-16; TC 2, Cary, NC, USA) with our additional added software, were compared with those derived by a high-resolution laser scanner (Vitus Smart XXL; Human Solutions North America, Cary, NC, USA). Both imaging systems were compared with additional linear (stadiometer-derived height) and volumetric (total volume, air-displacement plethysmography) measurements. Subjects (n=101) were healthy children (age ≥5 years) and adults varying in body mass index.Results:Representative linear (4), circumferential (6), volumetric (3) and surface area (1) measurements made by the Kinect-based device showed a consistent pattern relative to the laser system: high correlations (R 2 s= 0.70-0.99, all P<0.001); 1-3% differences for large linear (for example, height, X±s.d., -1.4±0.5%), circumferential (for example, waist circumference, -2.1±1.8%), volume (for example, total body, -0.8±2.2%) and surface area (whole-body, -1.7±2.0%) estimates. By contrast, mean measurement differences were substantially larger for small structures (for example, forearm volume, 31.3±31.4%).Conclusions:Low-cost 3D Kinect-based imaging systems have the potential for providing automated accurate anthropometric and related body measurements for relatively large components; further hardware and software developments may be able to improve system small-component resolution.
Publication Source (Journal or Book title)
European Journal of Clinical Nutrition
First Page
475
Last Page
481
Recommended Citation
Soileau, L., Bautista, D., Johnson, C., Gao, C., Zhang, K., Li, X., Heymsfield, S., Thomas, D., & Zheng, J. (2016). Automated anthropometric phenotyping with novel Kinect-based three-dimensional imaging method: Comparison with a reference laser imaging system. European Journal of Clinical Nutrition, 70 (4), 475-481. https://doi.org/10.1038/ejcn.2015.132