Literature DB >> 33680490

Digital anthropometry for body circumference measurements: Toward the development of universal three-dimensional optical system analysis software.

Sima Sobhiyeh1, Samantha Kennedy1, Alexander Dunkel2, Marcelline E Dechenaud2, Jerome A Weston2, John Shepherd3, Peter Wolenski2, Steven B Heymsfield1.   

Abstract

BACKGROUND/
OBJECTIVE: Digital anthropometric (DA) assessments are increasingly being administered with three-dimensional (3D) optical devices in clinical settings that manage patients with obesity and related metabolic disorders. However, anatomic measurement sites are not standardized across manufacturers, precluding use of published reference values and pooling of data across research centers. SUBJECTS/
METHODS: This study aimed to develop universal 3D analysis software by applying novel programming strategies capable of producing device-independent DA estimates that agree with conventional anthropometric (CA) measurements made at well-defined anatomic sites. A series of technical issues related to proprietary methods of 3D geometrical reconstruction and image analysis were addressed in developing major software components. To evaluate software accuracy, comparisons were made to CA circumference measurements made with a flexible tape at eleven standard anatomic sites in up to 35 adults scanned with three different commercial 3D optical devices.
RESULTS: Overall, group mean CA and DA values across the three systems were in good agreement, with ∼2 cm systematic differences; CA and DA estimates were highly correlated (all p-values <0.01); root-mean square errors were low (0.51-3.27 cm); and CA-DA bias tended to be small, but significant depending on anatomic site and device.
CONCLUSIONS: Availability of this software, with future refinements, has the potential to facilitate clinical applications and creation of large pooled uniform anthropometric databases.
© 2020 The Authors. Obesity Science & Practice published by World Obesity and The Obesity Society and John Wiley & Sons Ltd.

Entities:  

Keywords:  anthropometry; nutritional assessment; three‐dimensional optical imaging; waist circumference

Year:  2020        PMID: 33680490      PMCID: PMC7909596          DOI: 10.1002/osp4.467

Source DB:  PubMed          Journal:  Obes Sci Pract        ISSN: 2055-2238


  16 in total

1.  Errors in landmarking and the evaluation of the accuracy of traditional and 3D anthropometry.

Authors:  Makiko Kouchi; Masaaki Mochimaru
Journal:  Appl Ergon       Date:  2010-10-13       Impact factor: 3.661

2.  Reliability of a 3D Body Scanner for Anthropometric Measurements of Central Obesity.

Authors:  Jose Medina-Inojosa; Virend K Somers; Taiwo Ngwa; Ling Hinshaw; Francisco Lopez-Jimenez
Journal:  Obes Open Access       Date:  2016-10-06

Review 3.  Body composition and morphological assessment of nutritional status in adults: a review of anthropometric variables.

Authors:  A M Madden; S Smith
Journal:  J Hum Nutr Diet       Date:  2014-11-25       Impact factor: 3.089

4.  Detailed 3-dimensional body shape features predict body composition, blood metabolites, and functional strength: the Shape Up! studies.

Authors:  Bennett K Ng; Markus J Sommer; Michael C Wong; Ian Pagano; Yilin Nie; Bo Fan; Samantha Kennedy; Brianna Bourgeois; Nisa Kelly; Yong E Liu; Phoenix Hwaung; Andrea K Garber; Dominic Chow; Christian Vaisse; Brian Curless; Steven B Heymsfield; John A Shepherd
Journal:  Am J Clin Nutr       Date:  2019-12-01       Impact factor: 7.045

5.  Waist and hip circumferences have independent and opposite effects on cardiovascular disease risk factors: the Quebec Family Study.

Authors:  J C Seidell; L Pérusse; J P Després; C Bouchard
Journal:  Am J Clin Nutr       Date:  2001-09       Impact factor: 7.045

6.  Independent and opposite associations of waist and hip circumferences with diabetes, hypertension and dyslipidemia: the AusDiab Study.

Authors:  M B Snijder; P Z Zimmet; M Visser; J M Dekker; J C Seidell; J E Shaw
Journal:  Int J Obes Relat Metab Disord       Date:  2004-03

7.  Is waist circumference a useful measure in predicting health outcomes in the elderly?

Authors:  J Woo; S C Ho; A L M Yu; A Sham
Journal:  Int J Obes Relat Metab Disord       Date:  2002-10

8.  Hole Filling in 3D Scans for Digital Anthropometric Applications.

Authors:  Sima Sobhiyeh; Marcelline Dechenaud; Alexander Dunkel; Margarite LaBorde; Samantha Kennedy; John Shepherd; Steven Heymsfield; Peter Wolenski
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2019-07

9.  Body shape in American and British adults: between-country and inter-ethnic comparisons.

Authors:  J C K Wells; T J Cole; D Bruner; P Treleaven
Journal:  Int J Obes (Lond)       Date:  2007-07-31       Impact factor: 5.095

10.  Optical imaging technology for body size and shape analysis: evaluation of a system designed for personal use.

Authors:  Samantha Kennedy; Phoenix Hwaung; Nisa Kelly; Yong E Liu; Sima Sobhiyeh; Moonseong Heo; John A Shepherd; Steven B Heymsfield
Journal:  Eur J Clin Nutr       Date:  2019-09-24       Impact factor: 4.016

View more
  5 in total

Review 1.  Digital Anthropometry for Body Circumference Measurements: European Phenotypic Variations throughout the Decades.

Authors:  Marco Alessandro Minetto; Angelo Pietrobelli; Chiara Busso; Jonathan P Bennett; Andrea Ferraris; John A Shepherd; Steven B Heymsfield
Journal:  J Pers Med       Date:  2022-05-30

2.  Anthropometric evaluation of a 3D scanning mobile application.

Authors:  Brooke Smith; Cassidy McCarthy; Marcelline E Dechenaud; Michael C Wong; John Shepherd; Steven B Heymsfield
Journal:  Obesity (Silver Spring)       Date:  2022-05-02       Impact factor: 9.298

3.  Test/Retest Reliability and Validity of Remote vs. In-Person Anthropometric and Physical Performance Assessments in Cancer Survivors and Supportive Partners.

Authors:  Teri W Hoenemeyer; William W Cole; Robert A Oster; Dorothy W Pekmezi; Andrea Pye; Wendy Demark-Wahnefried
Journal:  Cancers (Basel)       Date:  2022-02-21       Impact factor: 6.575

4.  Smartphone camera based assessment of adiposity: a validation study.

Authors:  Maulik D Majmudar; Siddhartha Chandra; Kiran Yakkala; Samantha Kennedy; Amit Agrawal; Mark Sippel; Prakash Ramu; Apoorv Chaudhri; Brooke Smith; Antonio Criminisi; Steven B Heymsfield; Fatima Cody Stanford
Journal:  NPJ Digit Med       Date:  2022-06-29

5.  Normalized sensitivity of multi-dimensional body composition biomarkers for risk change prediction.

Authors:  A Criminisi; N Sorek; S B Heymsfield
Journal:  Sci Rep       Date:  2022-07-20       Impact factor: 4.996

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.