Reliability of 3D laser-based anthropometry and comparison with classical anthropometry

Impact of occlusal stabilization splints on global body posture: a prospective clinical trial

OBJECTIVES

Body posture of patients with temporomandibular disorders (TMD) has been investigated using different methods, whereas outcome and conclusions were controversial. The present clinical trial aimed to investigate the effects of splint therapy on global body posture.

MATERIALS AND METHODS

24 subjects (20 females, 4 males; age 24.2 ± 4.0 years) with TMD symptoms were examined clinically (RDC/TMD) and subsequently, splint fabrication was initiated. Along with routine therapy, all subjects underwent three-dimensional pre- and post-treatment full body scans in standing and upright sitting posture using a Vitus Smart XXL 3D scanner. Each scan was acquired in triplicate and evaluated in duplicate, measuring twelve standing and nine sitting postural parameters. Influencing factors were analyzed using analysis of variance (ANOVA), and additional Bland-Altman analyses verified the significance of the ANOVA results.

RESULTS

The increase of Forward Head angles and the decrease of Round Shoulders angles were consistent for both positions and sides. Forward Head angles were significantly influenced by limited mandibular mobility and myofascial pain. Round Shoulders angles showed a significant correlation with myofascial pain, joint noises and the absence of limited mandibular mobility.

CONCLUSION

The influence of occlusal splints on global posture is limited and only small effects on cervicocranial parameters were found. In the present study, the average head position of post treatment measurements was more centered on the body's core, whereas the shoulders were tilted more anteriorly.

CLINICAL RELEVANCE

Understanding the limited influence of occlusal splints on cervicocranial parameters underscores the need for multimodal treatment strategies for TMD patients.

Intra-rater and inter-rater reliability of 3D facial measurements

Three-dimensional (3D) body scanning technology has applications for obtaining anthropometric data in human-centered and product development fields. The reliability of 3D measurements gathered from 3D scans must be assessed to understand the degree to which this technology is appropriate for use in place of manual anthropometric methods. The intra- and inter-rater reliabilities of 3D facial measurements were assessed among four novice raters using 3D landmarking. Intraclass correlation coefficient (ICC) statistics were calculated for the 3D measurement data collected in three phases to assess baseline reliabilities and improvements in reliabilities as the result of additional training and experience. Based on the results of this study, the researchers found that the collection of 3D measurement data, by multiple raters and using 3D landmarking methods, yielded a high percentage of ICC statistics in the good to excellent (>0.75 ICC) reliability range. Rater training and experience were important considerations in improving intra- and inter-rater reliabilities.

Development and cross-validation of a circumference-based predictive equation to estimate body fat in an active population

Objective

The U.S. Army uses sex-specific circumference-based prediction equations to estimate percent body fat (%BF) to evaluate adherence to body composition standards. The equations are periodically evaluated to ensure that they continue to accurately assess %BF in a diverse population. The objective of this study was to develop and validate alternative field expedient equations that may improve upon the current Army Regulation (AR) body fat (%BF) equations.

Methods

Body size and composition were evaluated in a representatively sampled cohort of 1904 active-duty Soldiers (1261 Males, 643 Females), using dual-energy X-ray absorptiometry (%BFDXA), and circumferences obtained with 3D imaging and manual measurements. Sex stratified linear prediction equations for %BF were constructed using internal cross validation with %BFDXA as the criterion measure. Prediction equations were evaluated for accuracy and precision using root mean squared error, bias, and intraclass correlations. Equations were externally validated in a convenient sample of 1073 Soldiers.

Results

Three new equations were developed using one to three circumference sites. The predictive values of waist, abdomen, hip circumference, weight and height were evaluated. Changing from a 3-site model to a 1-site model had minimal impact on measurements of model accuracy and performance. Male-specific equations demonstrated larger gains in accuracy, whereas female-specific equations resulted in minor improvements in accuracy compared to existing AR equations. Equations performed similarly in the second external validation cohort.

Conclusions

The equations developed improved upon the current AR equation while demonstrating robust and consistent results within an external population. The 1-site waist circumference-based equation utilized the abdominal measurement, which aligns with associated obesity related health outcomes. This could be used to identify individuals at risk for negative health outcomes for earlier intervention.

Associations between 3D surface scanner derived anthropometric measurements and body composition in a cross-sectional study

BACKGROUND

3D laser-based photonic scanners are increasingly used in health studies to estimate body composition. However, too little is known about whether various 3D body scan measures estimate body composition better than single standard anthropometric measures, and which body scans best estimate it. Furthermore, little is known about differences by sex and age.

METHODS

105 men and 96 women aged between 18 and 90 years were analysed. Bioelectrical Impedance Analysis was used to estimate whole relative fat mass (RFM), visceral adipose tissue (VAT) and skeletal muscle mass index (SMI). An Anthroscan VITUSbodyscan was used to obtain 3D body scans (e.g. volumes, circumferences, lengths). To reduce the number of possible predictors that could predict RFM, VAT and SMI backward elimination was performed. With these selected predictors linear regression on the respective body compositions was performed and the explained variations were compared with models using standard anthropometric measurements (Body Mass Index (BMI), waist circumference (WC) and waist-to-height-ratio (WHtR)).

RESULTS

Among the models based on standard anthropometric measures, WC performed better than BMI and WHtR in estimating body composition in men and women. The explained variations in models including body scan variables are consistently higher than those from standard anthropometrics models, with an increase in explained variations between 5% (RFM for men) and 10% (SMI for men). Furthermore, the explained variation of body composition was additionally increased when age and lifestyle variables were added. For each of the body composition variables, the number of predictors differed between men and women, but included mostly volumes and circumferences in the central waist/chest/hip area and the thighs.

CONCLUSIONS

3D scan models performed better than standard anthropometric measures models to predict body composition. Therefore, it is an advantage for larger health studies to look at body composition more holistically using 3D full body surface scans.

Laser-Based 3D Body Scanning Reveals a Higher Prevalence of Abdominal Obesity than Tape Measurements: Results from a Population-Based Sample

BACKGROUND

The global obesity epidemic is a major public health concern, and accurate diagnosis is essential for identifying at-risk individuals. Three-dimensional (3D) body scanning technology offers several advantages over the standard practice of tape measurements for diagnosing obesity. This study was conducted to validate body scan data from a German population-based cohort and explore clinical implications of this technology in the context of metabolic syndrome.

METHODS

We performed a cross-sectional analysis of 354 participants from the Study of Health in Pomerania that completed a 3D body scanning examination. The agreement of anthropometric data obtained from 3D body scanning with manual tape measurements was analyzed using correlation analysis and Bland-Altman plots. Classification agreement regarding abdominal obesity based on IDF guidelines was assessed using Cohen's kappa. The association of body scan measures with metabolic syndrome components was explored using correlation analysis.

RESULTS

Three-dimensional body scanning showed excellent validity with slightly larger values that presumably reflect the true circumferences more accurately. Metabolic syndrome was highly prevalent in the sample (31%) and showed strong associations with central obesity. Using body scan vs. tape measurements of waist circumference for classification resulted in a 16% relative increase in the prevalence of abdominal obesity (61.3% vs. 52.8%).

CONCLUSIONS

These results suggest that the prevalence of obesity may be underestimated using the standard method of tape measurements, highlighting the need for more accurate approaches.

System for Estimation of Human Anthropometric Parameters Based on Data from Kinect v2 Depth Camera

Anthropometric measurements of the human body are an important problem that affects many aspects of human life. However, anthropometric measurement often requires the application of an appropriate measurement procedure and the use of specialized, sometimes expensive measurement tools. Sometimes the measurement procedure is complicated, time-consuming, and requires properly trained personnel. This study aimed to develop a system for estimating human anthropometric parameters based on a three-dimensional scan of the complete body made with an inexpensive depth camera in the form of the Kinect v2 sensor. The research included 129 men aged 18 to 28. The developed system consists of a rotating platform, a depth sensor (Kinect v2), and a PC computer that was used to record 3D data, and to estimate individual anthropometric parameters. Experimental studies have shown that the precision of the proposed system for a significant part of the parameters is satisfactory. The largest error was found in the waist circumference parameter. The results obtained confirm that this method can be used in anthropometric measurements.

Accuracy of a handheld 3D imaging system for child anthropometric measurements in population-based household surveys and surveillance platforms: an effectiveness validation study in Guatemala, Kenya, and China

BACKGROUND

An efficacy evaluation of the AutoAnthro system to measure child (0-59 months) anthropometry in the United States found 3D imaging performed as well as gold-standard manual measurements for biological plausibility and precision.

OBJECTIVES

We conducted an effectiveness evaluation of the accuracy of the AutoAnthro system to measure 0- to 59-month-old children's anthropometry in population-based surveys and surveillance systems in households in Guatemala and Kenya and in hospitals in China.

METHODS

The evaluation was done using health or nutrition surveillance system platforms among 600 children aged 0-59 months (Guatemala and Kenya) and 300 children aged 0-23 months (China). Field team anthropometrists and their assistants collected manual and scan anthropometric measurements, including length or height, midupper arm circumference (MUAC), and head circumference (HC; China only), from each child. An anthropometry expert and assistant later collected both manual and scan anthropometric measurements on the same child. The expert manual measurements were considered the standard compared to field team scans.

RESULTS

Overall, in Guatemala, Kenya, and China, for interrater accuracy, the average biases for length or height were -0.3 cm, -1.9 cm, and -6.2 cm, respectively; for MUAC were 0.9 cm, 1.2 cm, and -0.8 cm, respectively; and for HC was 2.4 cm in China. The inter-technical errors of measurement (inter-TEMs) for length or height were 2.8 cm, 3.4 cm, 5.5 cm, respectively; for MUAC were 1.1 cm, 1.5 cm, and 1.0 cm, respectively; and for HC was 2.8 cm in China. For intrarater precision, the absolute mean difference and intra-TEM (interrater, intramethod TEM) were 0.1 cm for all countries for all manual measurements. For scans, overall, absolute mean differences for length or height were 0.4-0.6 cm; for MUAC were 0.1-0.1 cm; and for HC was 0.4 cm. For the intra-TEM, length or height was 0.5 cm in Guatemala and China and 0.7 cm in Kenya, and other measurements were ≤0.3 cm.

CONCLUSIONS

Understanding the factors that cause the many poor scan results and how to correct them will be needed prior to using this instrument in routine, population-based survey and surveillance systems.

Modelling of human torso shape variation inferred by geometric morphometrics

Traditional body measurement techniques are commonly used to assess physical health; however, these approaches do not fully represent the complex shape of the human body. Three-dimensional (3D) imaging systems capture rich point cloud data that provides a representation of the surface of 3D objects and have been shown to be a potential anthropometric tool for use within health applications. Previous studies utilising 3D imaging have only assessed body shape based on combinations and relative proportions of traditional body measures, such as lengths, widths and girths. Geometric morphometrics (GM) is an established framework used for the statistical analysis of biological shape variation. These methods quantify biological shape variation after the effects of non-shape variation-location, rotation and scale-have been mathematically held constant, otherwise known as the Procrustes paradigm. The aim of this study was to determine whether shape measures, identified using geometric morphometrics, can provide additional information about the complexity of human morphology and underlying mass distribution compared to traditional body measures. Scale-invariant features of torso shape were extracted from 3D imaging data of 9,209 participants form the LIFE-Adult study. Partial least squares regression (PLSR) models were created to determine the extent to which variations in human torso shape are explained by existing techniques. The results of this investigation suggest that linear combinations of body measures can explain 49.92% and 47.46% of the total variation in male and female body shape features, respectively. However, there are also significant amounts of variation in human morphology which cannot be identified by current methods. These results indicate that Geometric morphometric methods can identify measures of human body shape which provide complementary information about the human body. The aim of future studies will be to investigate the utility of these measures in clinical epidemiology and the assessment of health risk.

First genome-wide association study of 99 body measures derived from 3-dimensional body scans

Body height, body mass index, hip and waist circumference are important risk factors or outcome variables in clinical and epidemiological research with complex underlying genetics. However, these classical anthropometric traits represent only a very limited view on the human body and other traits with potentially higher functional specificity are not yet studied to a larger extent. Participants of LIFE-Adult were assessed by three-dimensional body scanner VITUS XXL determining 99 high-quality anthropometric traits in parallel. Genotyping was performed by Axiom Genome-Wide CEU 1 Array Plate microarray technology and imputation was done using 1000 Genomes phase 3 reference panel. Combined phenotype and genetic information are available for a total of 7,562 participants. Largest heritabilities were estimated for height traits (maximum heritability with h² = 44% for neck height) and 61 traits achieved values larger than 20%. By genome-wide analyses, we identified 16 loci associated with at least one of the 99 traits. Ten of these loci were not described for association with classical anthropometric traits so far. The strongest novel association was observed for 7p14.3 (rs11979006, P = 2.12 × 10⁻⁹) for the trait Back Width with ZNRF2 as the most plausible candidate gene. Loci established for association with classical anthropometric traits were subjected to anthropometric phenome-wide association analysis. From the reported 709 loci, 211 are co-associated with body scanner traits (enrichment: OR = 1.96, P = 1.08 × 10⁻⁶¹). We conclude that genetics of 3D laser-based anthropometry is promising to identify novel loci and to improve the functional understanding of established ones.

A method for increasing 3D body scanning's precision: Gryphon and consecutive scanning

The fashion industry cannot use 3 D Body Scanning to create custom garment patterns because its measurements fail to meet ISO 20685:2010's tolerances. To advance 3 D Body Scanning's precision, we present Gryphon: an algorithm that removes the two most extreme measurements from five body scans; removing potentially erroneous data. We assess Gryphon's precision against current industry practice, determine if consecutive and non-consecutive data capture influences precision, and determine 3 D Body Scanning's inherent imprecision inherent. We analyse 97 participants over 121 industry-standard measurements for consecutive and non-consecutive data-capture through MANOVA statistical analysis. Under current industry practice, only one measurement meets ISO 20685. However, under Gryphon and consecutive scanning, 97.5% of measurements meet ISO 20685. We also prove that the body's in-scan movement does not affect reliability. Ultimately, we offer the fashion industry, ergonomists, and practitioners an accessible method to increase 3 D Body Scanning's precision at a level unavailable under previous methods. Practitioner Summary: Ergonomists need precise data, yet we prove 0% of 3 D Body Scanning's measurements meet ISO 20685's tolerances. Our analysis of 97 participants scans, shows consecutive scanning is necessary to achieve data suitable for anthropometric applications. We develop the Gryphon process with consecutive scanning, making 97.3% of measurements meet ISO 20685. Abbreviations: ISO: International Organisation for Standards; Three Dimensional: 3D; MANOVA: Multivariate analysis of variance.

Prediction of military combat clothing size using decision trees and 3D body scan data

AIM

To determine how well decision tree models can predict tailor-assigned uniform sizes using anthropometry data from the New Zealand Defence Force Anthropometry Survey (NZDFAS). This information may inform automatic sizing systems for military personnel.

METHODS

Anthropometric data from two separate samples of the New Zealand Defence Force military were used. Data on Army personnel from the NZDFAS (n = 583) were used to develop a series of shirt- and trouser-size prediction models based on decision trees. Different combinations of physical, automatic, and post-processed measurements (the latter two derived from a 3D body scan) were trialled, and the models with the highest cross-validation accuracy were retained. The accuracy of these models were then tested on an independent sample of Army recruits (n = 154).

RESULTS

The automated measurement method (measurements derived automatically by the body scanner software) were the best predictors of shirt size (58.1% accuracy) and trouser size (61.7%), with body weight and waist girth being the strongest predictors. Clothing sizes that were incorrectly predicted by the model where generally one size above or below the tailor-predicted size.

CONCLUSIONS

Anthropometry measurements, when used with decision tree models, show promise for classifying clothing size. Methodological changes such as fitting gender-specific models, using additional anthropometry variables, and testing other data mining techniques are avenues for future work. More research is required before fully automated body scanning is a viable option for obtaining fast and accurate clothing sizes for military clothing and logistics departments.

Comparison of Body Scanner and Manual Anthropometric Measurements of Body Shape: A Systematic Review

Anthropometrics are a set of direct quantitative measurements of the human body’s external dimensions, which can be used as indirect measures of body composition. Due to a number of limitations of conventional manual techniques for the collection of body measurements, advanced systems using three-dimensional (3D) scanners are currently being employed, despite being a relatively new technique. A systematic review was carried out using Pubmed, Medline and the Cochrane Library to assess whether 3D scanners offer reproducible, reliable and accurate data with respect to anthropometrics. Although significant differences were found, 3D measurements correlated strongly with measurements made by conventional anthropometry, dual-energy X-ray absorptiometry (DXA) and air displacement plethysmography (ADP), among others. In most studies (61.1%), 3D scanners were more accurate than these other techniques; in fact, these scanners presented excellent accuracy or reliability. 3D scanners allow automated, quick and easy measurements of different body tissues. Moreover, they seem to provide reproducible, reliable and accurate data that correlate well with the other techniques used.

Associations between relative body fat and areal body surface roughness characteristics in 3D photonic body scans-a proof of feasibility

INTRODUCTION

A reliable and accurate estimate of the percentage and distribution of adipose tissue in the human body is essential for evaluating the risk of developing chronic and noncommunicable diseases. A precise and differentiated method, which at the same time is fast, noninvasive, and straightforward to perform, would, therefore, be desirable. We sought a new approach to this research area by linking a person's relative body fat with their body surface's areal roughness characteristics.

MATERIALS AND METHODS

For this feasibility study, we compared areal surface roughness characteristics, assessed from 3D photonic full-body scans of 76 Swiss young men, and compared the results with body impedance-based estimates of relative body fat. We developed an innovative method for characterizing the areal surface roughness distribution of a person's entire body, in a similar approach as it is currently used in geoscience or material science applications. We then performed a statistical analysis using different linear and stepwise regression models.

RESULTS

In a stepwise regression analysis of areal surface roughness frequency tables, a combination of standard deviation, interquartile range, and mode showed the best association with relative body fat (R² = 0.55, p < 0.0001). The best results were achieved by calculating the arithmetic mean height, capable of explaining up to three-quarters of the variance in relative body fat (R² = 0.74, p < 0.001).

DISCUSSION AND CONCLUSION

This study shows that areal surface roughness characteristics assessed from 3D photonic whole-body scans associate well with relative body fat, therefore representing a viable new approach to improve current 3D scanner-based methods for determining body composition and obesity-associated health risks. Further investigations may validate our method with other data or provide a more detailed understanding of the relation between the body's areal surface characteristics and adipose tissue distribution by including larger and more diverse populations or focusing on particular body segments.

How shape-based anthropometry can complement traditional anthropometric techniques: a cross-sectional study

Manual anthropometrics are used extensively in medical practice and epidemiological studies to assess an individual's health. However, traditional techniques reduce the complicated shape of human bodies to a series of simple size measurements and derived health indices, such as the body mass index (BMI), the waist-hip-ratio (WHR) and waist-by-height0.5 ratio (WHT.5R). Three-dimensional (3D) imaging systems capture detailed and accurate measures of external human form and have the potential to surpass traditional measures in health applications. The aim of this study was to investigate how shape measurement can complement existing anthropometric techniques in the assessment of human form. Geometric morphometric methods and principal components analysis were used to extract independent, scale-invariant features of torso shape from 3D scans of 43 male participants. Linear regression analyses were conducted to determine whether novel shape measures can complement anthropometric indices when estimating waist skinfold thickness measures. Anthropometric indices currently used in practice explained up to 52.2% of variance in waist skinfold thickness, while a combined regression model using WHT.5R and shape measures explained 76.5% of variation. Measures of body shape provide additional information regarding external human form and can complement traditional measures currently used in anthropometric practice to estimate central adiposity.

Machine learning prediction of combat basic training injury from 3D body shape images

Introduction

Athletes and military personnel are both at risk of disabling injuries due to extreme physical activity. A method to predict which individuals might be more susceptible to injury would be valuable, especially in the military where basic recruits may be discharged from service due to injury. We postulate that certain body characteristics may be used to predict risk of injury with physical activity.

Methods

US Army basic training recruits between the ages of 17 and 21 (N = 17,680, 28% female) were scanned for uniform fitting using the 3D body imaging scanner, Human Solutions of North America at Fort Jackson, SC. From the 3D body imaging scans, a database consisting of 161 anthropometric measurements per basic training recruit was used to predict the probability of discharge from the US Army due to injury. Predictions were made using logistic regression, random forest, and artificial neural network (ANN) models. Model comparison was done using the area under the curve (AUC) of a ROC curve.

Results

The ANN model outperformed two other models, (ANN, AUC = 0.70, [0.68,0.72], logistic regression AUC = 0.67, [0.62,0.72], random forest AUC = 0.65, [0.61,0.70]).

Conclusions

Body shape profiles generated from a three-dimensional body scanning imaging in military personnel predicted dischargeable physical injury. The ANN model can be programmed into the scanner to deliver instantaneous predictions of risk, which may provide an opportunity to intervene to prevent injury.

Multiple measures derived from 3D photonic body scans improve predictions of fat and muscle mass in young Swiss men

INTRODUCTION

Digital tools like 3D laser-based photonic scanners, which can assess external anthropometric measurements for population based studies, and predict body composition, are gaining in importance. Here we focus on a) systematic deviation between manually determined and scanned standard measurements, b) differences regarding the strength of association between these standard measurements and body composition, and c) improving these predictions of body composition by considering additional scan measurements.

METHODS

We analysed 104 men aged 19-23. Bioelectrical Impedance Analysis was used to estimate whole body fat mass, visceral fat mass and skeletal muscle mass (SMM). For the 3D body scans, an Anthroscan VITUSbodyscan was used to automatically obtain 90 body shape measurements. Manual anthropometric measurements (height, weight, waist circumference) were also taken.

RESULTS

Scanned and manually measured height, waist circumference, waist-to-height-ratio, and BMI were strongly correlated (Spearman Rho>0.96), however we also found systematic differences. When these variables were used to predict body fat or muscle mass, explained variation and prediction standard errors were similar between scanned and manual measurements. The univariable predictions performed well for both visceral fat (r2 up to 0.92) and absolute fat mass (AFM, r2 up to 0.87) but not for SMM (r2 up to 0.54). Of the 90 body scanner measures used in the multivariable prediction models, belly circumference and middle hip circumference were the most important predictors of body fat content. Stepwise forward model selection using the AIC criterion showed that the best predictive power (r2 up to 0.99) was achieved with models including 49 scanner measurements.

CONCLUSION

The use of a 3D full body scanner produced results that strongly correlate to manually measured anthropometric measures. Predictions were improved substantially by including multiple measurements, which can only be obtained with a 3D body scanner, in the models.

The aging human body shape

Body shape and composition are heterogeneous among humans with possible impact for health. Anthropometric methods and data are needed to better describe the diversity of the human body in human populations, its age dependence, and associations with health risk. We applied whole-body laser scanning to a cohort of 8499 women and men of age 40–80 years within the frame of the LIFE (Leipzig Research Center for Civilization Diseases) study aimed at discovering health risk in a middle European urban population. Body scanning delivers multidimensional anthropometric data, which were further processed by machine learning to stratify the participants into body types. We here applied this body typing concept to describe the diversity of body shapes in an aging population and its association with physical activity and selected health and lifestyle factors. We find that aging results in similar reshaping of female and male bodies despite the large diversity of body types observed in the study. Slim body shapes remain slim and partly tend to become even more lean and fragile, while obese body shapes remain obese. Female body shapes change more strongly than male ones. The incidence of the different body types changes with characteristic Life Course trajectories. Physical activity is inversely related to the body mass index and decreases with age, while self-reported incidence for myocardial infarction shows overall the inverse trend. We discuss health risks factors in the context of body shape and its relation to obesity. Body typing opens options for personalized anthropometry to better estimate health risk in epidemiological research and future clinical applications.

[Anthropometric measures in the German National Cohort-more than weight and height]

High levels of adiposity in the population have a major impact on various diseases, but previous epidemiologic studies have largely been restricted to simple anthropometric measures such as the body mass index (BMI), an imperfect predictor of disease risk. There is a critical need for the use of improved measures of relative weight and body composition in large-scale, population-based research.The current article presents initial descriptive results of body composition and fat distribution based on the midterm baseline dataset of the German National Cohort, which included 101,817 participants who were examined in 18 study centers in Germany between March 2014 and March 2017. The anthropometric measures encompassed body weight, height, waist and hip circumference, bioelectrical impedance analysis (BIA), sonography of abdominal adipose tissue, 3D-body scanning, and magnetic resonance imaging.BMI analyses showed that 46.2% of men and 29.7% of women were overweight and 23.5% of men and 21.2% of women were obese. On average, women in almost all age groups demonstrated more subcutaneous adipose tissue layer thickness than men. The mean values of visceral adipose tissue layer thickness, on the other hand, were higher among men than among women in all age groups and increased continuously across age groups in both sexes.The comprehensive assessment of body composition and fat distribution provides novel future opportunities for detailed epidemiologic analyses of overweight and adiposity in relation to the development of chronic diseases.

Body height and waist circumference of young Swiss men as assessed by 3D laser-based photonic scans and by manual anthropometric measurements

Overweight and obesity are considered among the major health concerns worldwide. The body mass index is a frequently used measure for overweight and obesity and is associated with common non-communicable diseases such as diabetes type II, cardiovascular diseases and certain cancers. However, the body mass index does not account for the distribution of body fat and relative fat to muscle mass. 3D laser-based photonic full body scans provide detailed information on various body circumferences, surfaces, and volumes as well as body height and weight (using an integrated scale). In the literature, body scans showed good feasibility, reliability, and validity, while also demonstrating a good correlation with health parameters linked to the metabolic syndrome. However, systematic differences between body scan derived measurements and manual measurements remain an issue. This study aimed to assess these systematic differences for body height, waist circumference, and body mass index using cross-sectional data from a homogenous sample of 52 young Swiss male volunteers. In addition to 3D laser-based photonic full body scans and correlative manual measurements, body fat distribution was assessed through bioelectrical impedance analysis. Overall, an excellent correlation was found between measurements of waist circumference and body mass index, and good correlation between body mass index and total fat mass, as well as between waist circumference and visceral fat mass as assessed by bioelectrical impedance analysis. Volunteers were shorter in height measured by body scan when compared to manual measurements. This systematic difference became smaller when volunteers stood in the scanner in a completely upright position with their feet together. Waist circumference was slightly smaller for manual measurements than for body scan derived values. This systematic difference was larger in overweight volunteers compared to leaner volunteers.

Body shape: Implications in the study of obesity and related traits

OBJECTIVES

The diagnosis and treatment of obesity are usually based on traditional anthropometric variables including weight, height, and several body perimeters. Here we present a three-dimensional (3D) image-based computational approach aimed to capture the distribution of abdominal adipose tissue as an aspect of shape rather than a relationship among classical anthropometric measures.

METHODS

A morphometric approach based on landmarks and semilandmarks placed upon the 3D torso surface was performed in order to quantify abdominal adiposity shape variation and its relation to classical indices. Specifically, we analyzed sets of body cross-sectional circumferences, collectively defining each, along with anthropometric data taken on 112 volunteers. Principal Component Analysis (PCA) was performed on 250 circumferences located along the abdominal region of each volunteer. An analysis of covariance model was used to compare shape variables (PCs) against anthropometric data (weight, height, and waist and hip circumferences).

RESULTS

The observed shape patterns were mainly related to nutritional status, followed by sexual dimorphism. PC1 (12.5%) and PC2 (7.5%) represented 20% of the total variation. In PCAs calculated independently by sex, linear regression analyses provide statistically significant associations between PC1 and the three classical indexes: body mass index, waist-to-height ratio, and waist-hip ratio.

CONCLUSION

Shape indicators predict well the behavior of classical markers, but also evaluate 3D and geometric features with more accuracy as related to the body shape under study. This approach also facilitates diagnosis and follow-up of therapies by using accessible 3D technology.

Development of a new 360-degree surface topography application

BACKGROUND

Surface-topography has been used for almost two decades in the radiation-free clinical evaluation of spinal posture. So far, it was limited to the analysis of back surface and spine. In order to better understand, diagnose and treat complex spinal pathologies, it is important to measure the whole torso.

RESEARCH QUESTION

Purpose of this study was to introduce and test an application that allows 360° reconstruction and analysis of the patient's torso.

METHODS

The application uses the information gathered from eight distinct scans and angles. For validation we used an Alderson phantom as an anthropomorphic body. Defined areas and volumes were measured by CT and surface-topography. Inter- and intra-rater reliability was tested in 35 healthy subjects by two observers.

RESULTS

The results revealed good correspondence between systems in the imaging and evaluation of the Alderson model (5.3-0.5%). Inter- (0.9-0.98) and intra-rater reliability (0.8-0.95) testing revealed good and excellent results in the detection of almost all body surface structures and measurement of areas and volumes. Only area and volume measurements using jugular notch as a reference showed partly moderate results in reliability (0.62-0.93) testing.

SIGNIFICANCE

We were able to introduce a novel 360° torso scan application using surface topography to reconstruct torso measurements. The results of our study showed its high validity and reliability. In the future, this application needs to be tested in patients with spinal pathologies. In summary, this new application may help to better understand, diagnose and treat patients with pathologies of torso and spine.

3D anthropometric assessment and perception of male body morphology in relation to physical strength

OBJECTIVES

The assessment of men's physical strength is an important part of human social perception, for which observers rely on different kinds of cues. However, besides previous studies being limited in considerable ways, as yet there is no comprehensive investigation of a range of somatometric measures in relation to both objectively measured and observer-perceived physical strength using valid stimuli.

METHODS

We examined observer-perceptions of physical strength from 3D body scans of n = 165 men, the usage and validity of somatometric measures as cues to strength, differences between strength ratings from stimuli presented on computer monitors vs in real-life size using a projector, and between male and female observers.

RESULTS

A medium-sized correlation between measured and perceived strength was found, partly mediated by target men's chest-to-hip ratio, body density, ankle girth, height, upper arm, and forearm girth. No significant differences between men's and women's strength perceptions or the method of stimuli presentation (computer monitor vs projector) emerged.

CONCLUSIONS

Our findings suggest that men's physical strength can be assessed with moderate accuracy from 3D body models and that some somatometric measures represent valid cues, which were used by observers, positively predicting both measured and perceived physical strength.

Perspective: Are We Ready to Measure Child Nutritional Status with Lasers?

The continued use of basic, manual anthropometric tools (e.g., boards and tapes) leaves anthropometry susceptible to human error. A potential solution, 3-dimensional (3D) imaging systems for anthropometry, has been around since the 1950s. In the 1980s, 3D imaging technology advanced from photographs to the use of lasers for body digitization; and by the 2000s, the falling price of 3D scanners made commercial application feasible. The garment sector quickly adopted imaging technology for surveys because of the need for numerous measurements and large sample sizes. In the health sector, 3D imaging for anthropometry was not widely adopted; its use was limited to research and specialized purposes. The different cost and logistical requirements for measurement in the garment and health sectors help to explain why the technology was adopted in one sector and not the other. Despite reductions, the price of 3D imaging systems remained a barrier to the use of 3D imaging for regular nutritional assessment in the health sector. Additional barriers in the health sector were that imaging systems required dedicated space and were not designed for capturing measurements in young children. In recent years, the development of light-coding technology may have removed these barriers, and a handheld imaging system was developed specifically for young children. There are not yet recommendations to replace manual equipment with 3D imaging for nutritional assessment, and there is a need for more research on low-cost, handheld imaging systems-particularly research that evaluates the ability of 3D imaging to improve the quality of anthropometric data and indicators.

A machine learning approach relating 3D body scans to body composition in humans

A long-standing question in nutrition and obesity research involves quantifying the relationship between body fat and anthropometry. To date, the mathematical formulation of these relationships has relied on pairing easily obtained anthropometric measurements such as the body mass index (BMI), waist circumference, or hip circumference to body fat. Recent advances in 3D body shape imaging technology provides a new opportunity for quickly and accurately obtaining hundreds of anthropometric measurements within seconds, however, there does not yet exist a large diverse database that pairs these measurements to body fat. Herein, we leverage 3D scanned anthropometry obtained from a population of United States Army basic training recruits to derive four subpopulations of homogenous body shape archetypes using a combined principal components and cluster analysis. While the Army database was large and diverse, it did not have body composition measurements. Therefore, these body shape archetypes were paired to an alternate smaller sample of participants from the Pennington Biomedical Research Center in Baton Rouge, LA that were not only similarly imaged by the same 3D scanning machine, but also had concomitant measures of body composition by dual-energy X-ray absorptiometry body composition. With this enhanced ability to obtain anthropometry through 3D scanning quickly of large populations, our machine learning approach for pairing body shapes from large datasets to smaller datasets that also contain state-of-the-art body composition measurements can be extended to pair other health outcomes to 3D body shape anthropometry.

A collaborative, mixed-methods evaluation of a low-cost, handheld 3D imaging system for child anthropometry

3D imaging for body measurements is regularly used for design of garments and ergonomic products. The development of low‐cost 3D scanners provided an opportunity to extend the use of 3D imaging to the health sector. We developed and tested the AutoAnthro System, the first mobile, low‐cost, full‐body, 3D imaging system designed specifically for child anthropometry. This study evaluated the efficiency, invasiveness, and user experience of the AutoAnthro System. We used a mixed‐methods, collaborative approach that included a quantitative time‐motion study and qualitative interviews of anthropometrists. For cooperative children, anthropometrists considered the use of 3D imaging an easy, “streamlined experience,” but with uncooperative children, anthropometrists reported that capturing a good quality scan was out of their control. The mean time to complete a full set of scans was 68 s (standard deviation [SD] 29), compared with 135 s (SD 22) for a set of manual measurements (stature, head circumference, and arm circumference). We observed that crying was more common during manual measurement, and anthropometrist interviews confirmed that 3D imaging was less stressful for children than manual measurement. In a previous publication, we showed the potential of 3D imaging to produce reliable and accurate measurements. In this study, we found that anthropometrists were not ready to abandon manual equipment for 3D scanners because of difficulty in measuring uncooperative children. Revising the AutoAnthro System to address anthropometrists' concerns on capturing good quality scans of uncooperative children should help to facilitate widespread use of 3D imaging for child anthropometry.

Revisiting the United States Army body composition standards: a receiver operating characteristic analysis

BACKGROUND

The objective for percent body fat standards in the United States Army Body Composition Program (ABCP) is to ensure soldiers maintain optimal well-being and performance under all conditions. However, conducting large-scale experiments within the United States Army to evaluate the efficacy of the thresholds is challenging.

METHODS

A receiver operating characteristic (ROC) analysis with corresponding area under the curve (AUC) was performed on body mass index (BMI) and waist circumference to determine optimal gender-specific age cohort thresholds that meet ABCP percent body fat standards in the National Health and Nutrition Examination Survey (NHANES) III. A second dataset consisting of a cohort of basic training recruits (N = 20,896 soldiers, 28% female) with BMI and waist circumference measured using a 3D body image scanner was applied to calculate what percent of basic training recruits meet the ABCP percent body fat standards. Regression models to determine the contribution of different circumference sites to the predictions of percent body fat were developed using a database compiled at the New York Obesity Research Center (N = 500).

RESULTS

Optimal BMI thresholds ranged from 23.65 kg/m² (17-21-year-old cohort) to 26.55 kg/m² (40 and over age cohort) for males and 21.75 to 24.85 kg/m² for females. The AUC values were between 0.86 and 0.92. The waist circumference thresholds ranged 81.35 to 97.55 cm for males and 77.05 to 89.35 cm for females with AUC values between 0.90 and 0.91. These BMI thresholds were exceeded by 65% of male and 74% of female basic training recruits and waist circumference thresholds were exceeded by 73% of male and 85% of female recruits. The single circumference that contributed most to prediction of body fat was waist circumference in males and mid-thigh circumference in females.

CONCLUSIONS

The ABCP percent body fat thresholds yield BMI thresholds that are below the United States Army BMI standards, especially in females which suggests the ABCP percent body fat standards may be too restrictive. The United States Army percent body fat standards could instead be matched to existing national health guidelines.

Development of a positioning aid to reduce postural variability and errors in 3D whole body scan measurements

Three-dimensional (3D) body scanners have the potential to evaluate changes to the human form through different clothing configurations, the use of protective equipment, or the effects of medical interventions. To achieve this, scans of an individual need to be superimposed for each experimental condition. The literature highlights that one of the limiting factors is postural variability. This paper describes a newly developed 'positioning aid' that stabilises the posture during the scanning process and is invisible on scans. The results of a study evaluating the efficacy of the positioning aid showed that it reduces postural variability for all body parts in lateral and longitudinal directions. A reference test with a rigid mannequin indicated that the 'technical' variability due to the scanner hardware and software significantly contributes to the residual variability. Furthermore, the study showed that the newly developed positioning aid overall increased the precision of the software-assisted extraction of body dimensions.

Measurements agreement between low-cost and high-level handheld 3D scanners to scan the knee for designing a 3D printed knee brace

Use of additive manufacturing is growing rapidly in the orthotics field. This technology allows orthotics to be designed directly on digital scans of limbs. However, little information is available about scanners and 3D scans. The aim of this study is to look at the agreement between manual measurements, high-level and low-cost handheld 3D scanners. We took two manual measurements and three 3D scans with each scanner from 14 lower limbs. The lower limbs were divided into 17 sections of 30mm each from 180mm above the mid-patella to 300mm below. Time to record and to process the three 3D scans for scanners methods were compared with Student t-test while Bland-Altman plots were used to study agreement between circumferences of each section from the three methods. The record time was 97s shorter with high-level scanner than with the low-cost (p = .02) while the process time was nine times quicker with the low-cost scanner (p < .01). An overestimation of 2.5mm was found in high-level scanner compared to manual measurement, but with a better repeatability between measurements. The low-cost scanner tended to overestimate the circumferences from 0.1% to 1.5%, overestimation being greater for smaller circumferences. In conclusion, 3D scanners provide more information about the shape of the lower limb, but the reliability depends on the 3D scanner and the size of the scanned segment. Low-cost scanners could be useful for clinicians because of the simple and fast process, but attention should be focused on accuracy, which depends on the scanned body segment.

Body typing of children and adolescents using 3D-body scanning

Three-dimensional (3D-) body scanning of children and adolescents allows the detailed study of physiological development in terms of anthropometrical alterations which potentially provide early onset markers for obesity. Here, we present a systematic analysis of body scanning data of 2,700 urban children and adolescents in the age range between 5 and 18 years with the special aim to stratify the participants into distinct body shape types and to describe their change upon development. In a first step, we extracted a set of eight representative meta-measures from the data. Each of them collects a related group of anthropometrical features and changes specifically upon aging. In a second step we defined seven body types by clustering the meta-measures of all participants. These body types describe the body shapes in terms of three weight (lower, normal and overweight) and three age (young, medium and older) categories. For younger children (age of 5-10 years) we found a common 'early childhood body shape' which splits into three weight-dependent types for older children, with one or two years delay for boys. Our study shows that the concept of body types provides a reliable option for the anthropometric characterization of developing and aging populations.

Validity and intraobserver reliability of three-dimensional scanning compared with conventional anthropometry for children and adolescents from a population-based cohort study

BACKGROUND

Conventional anthropometric measurements are time consuming and require well trained medical staff. To use three-dimensional whole body laser scanning in daily clinical work, validity, and reliability have to be confirmed.

METHODS

We compared a whole body laser scanner with conventional anthropometry in a group of 473 children and adolescents from the Leipzig Research Centre for Civilization Diseases (LIFE-Child). Concordance correlation coefficients (CCC) were calculated separately for sex, weight, and age to assess validity. Overall CCC (OCCC) was used to analyze intraobserver reliability.

RESULTS

Body height and the circumferences of waist, hip, upper arm, and calf had an "excellent" (CCC ≥ 0.9); neck and thigh circumference, a "good" (CCC ≥ 0.7); and head circumference, a "low" (CCC < 0.5) degree of concordance over the complete study population. We observed dependencies of validity on sex, weight, and age. Intraobserver reliability of both techniques is "excellent" (OCCC ≥ 0.9).

CONCLUSION

Scanning is faster, requires less intensive staff training and provides more information. It can be used in an epidemiologic setting with children and adolescents but some measurements should be considered with caution due to reduced agreement with conventional anthropometry.

Comparison of 3D laser-based photonic scans and manual anthropometric measurements of body size and shape in a validation study of 123 young Swiss men

Background

Manual anthropometric measurements are time-consuming and challenging to perform within acceptable intra- and inter-individual error margins in large studies. Three-dimensional (3D) laser body scanners provide a fast and precise alternative: within a few seconds the system produces a 3D image of the body topography and calculates some 150 standardised body size measurements.

Objective

The aim was to enhance the small number of existing validation studies and compare scan and manual techniques based on five selected measurements. We assessed the agreement between two repeated measurements within the two methods, analysed the direct agreement between the two methods, and explored the differences between the techniques when used in regressions assessing the effect of health related determinants on body shape indices.

Methods

We performed two repeated body scans on 123 volunteering young men using a Vitus Smart XXL body scanner. We manually measured height, waist, hip, buttock, and chest circumferences twice for each participant according to the WHO guidelines. The participants also filled in a basic questionnaire.

Results

Mean differences between the two scan measurements were smaller than between the two manual measurements, and precision as well as intra-class correlation coefficients were higher. Both techniques were strongly correlated. When comparing means between both techniques we found significant differences: Height was systematically shorter by 2.1 cm, whereas waist, hip and bust circumference measurements were larger in the scans by 1.17–4.37 cm. In consequence, body shape indices also became larger and the prevalence of overweight was greater when calculated from the scans. Between 4.1% and 7.3% of the probands changed risk category from normal to overweight when classified based on the scans. However, when employing regression analyses the two measurement techniques resulted in very similar coefficients, confidence intervals, and p-values.

Conclusion

For performing a large number of measurements in a large group of probands in a short time, body scans generally showed good feasibility, reliability, and validity in comparison to manual measurements. The systematic differences between the methods may result from their technical nature (contact vs. non-contact).

Body surface assessment with 3D laser-based anthropometry: reliability, validation, and improvement of empirical surface formulae

Purpose

Body surface area is a physiological quantity relevant for many medical applications. In clinical practice, it is determined by empirical formulae. 3D laser-based anthropometry provides an easy and effective way to measure body surface area but is not ubiquitously available. We used data from laser-based anthropometry from a population-based study to assess validity of published and commonly used empirical formulae.

Methods

We performed a large population-based study on adults collecting classical anthropometric measurements and 3D body surface assessments (N = 1435). We determined reliability of the 3D body surface assessment and validity of 18 different empirical formulae proposed in the literature. The performance of these formulae is studied in subsets of sex and BMI. Finally, improvements of parameter settings of formulae and adjustments for sex and BMI were considered.

Results

3D body surface measurements show excellent intra- and inter-rater reliability of 0.998 (overall concordance correlation coefficient, OCCC was used as measure of agreement). Empirical formulae of Fujimoto and Watanabe, Shuter and Aslani and Sendroy and Cecchini performed best with excellent concordance with OCCC > 0.949 even in subgroups of sex and BMI. Re-parametrization of formulae and adjustment for sex and BMI slightly improved results.

Conclusion

In adults, 3D laser-based body surface assessment is a reliable alternative to estimation by empirical formulae. However, there are empirical formulae showing excellent results even in subgroups of sex and BMI with only little room for improvement.

Electronic supplementary material

The online version of this article (doi:10.1007/s00421-016-3525-5) contains supplementary material, which is available to authorized users.