title: Automated anthropometric phenotyping with novel Kinect-based three-dimensional imaging method: comparison with a reference laser imaging system.
abstract: OBJECTIVE
  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.
  
  
  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.
authors.affiliation: Department of Biomedical Engineering, Florida Institute of Technology, Melbourne, FL, USA.
authors.forename: L
authors.initials: L
authors.lastname: Soileau
authors.affiliation: Tulane University School of Medicine, New Orleans, LA, USA.
authors.forename: D
authors.initials: D
authors.lastname: Bautista
authors.affiliation: Body Composition Laboratory, Pennington Biomedical Research Center, Louisiana State University System, Baton Rouge, LA, USA.
authors.forename: C
authors.initials: C
authors.lastname: Johnson
authors.affiliation: Body Composition Laboratory, Pennington Biomedical Research Center, Louisiana State University System, Baton Rouge, LA, USA.
authors.forename: C
authors.initials: C
authors.lastname: Gao
authors.affiliation: Division of Electrical and Computer Engineering, School of Electrical Engineering and Computer Science, Louisiana State University, Baton Rouge, LA, USA.
authors.forename: K
authors.initials: K
authors.lastname: Zhang
authors.affiliation: Division of Electrical and Computer Engineering, School of Electrical Engineering and Computer Science, Louisiana State University, Baton Rouge, LA, USA.
authors.forename: X
authors.initials: X
authors.lastname: Li
authors.affiliation: Body Composition Laboratory, Pennington Biomedical Research Center, Louisiana State University System, Baton Rouge, LA, USA.
authors.forename: S B
authors.initials: SB
authors.lastname: Heymsfield
authors.affiliation: Department of Mathematics, Center for Quantitative Obesity Research, Montclair State University, Montclair, NJ, USA.
authors.forename: D
authors.initials: D
authors.lastname: Thomas
authors.affiliation: Body Composition Laboratory, Pennington Biomedical Research Center, Louisiana State University System, Baton Rouge, LA, USA.
authors.forename: J
authors.initials: J
authors.lastname: Zheng
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000886:Anthropometry / Q000379:methods*; D001827:Body Height; D015992:Body Mass Index; D049628:Body Size; D001835:Body Weight; D002648:Child; D002675:Child, Preschool; D005260:Female; D006801:Humans; D021621:Imaging, Three-Dimensional; D007834:Lasers; D016014:Linear Models; D008297:Male; D008875:Middle Aged; D010641:Phenotype; D012984:Software; D055105:Waist Circumference; D055815:Young Adult