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3D scan images (screenshots from the AnthroScan Professional software interface) with marked measures as assessed in this study. Yellow lines indicate the actual measuring site; purple lines indicate reference measurements. (a) body-height; (b) waist-girth, (c) high-waist-girth, (d) waist-band, (e) belly-circumference; (f) buttock-girth, (g) middle-hip, (h) high-hip-girth, (i) hip-girth, and (j) hip-thigh-girth (Picture: modified from Human Solutions GmbH)
Source publication
Body surface scanners (BS), which visualize a 3D image of the human body, facilitate the computation of numerous body measures, including height, waist circumference (WC) and hip circumference (HC). However, limited information is available regarding validity and reliability of these automated measurements (AM) and their correlation with parameters...
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Introduction:
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Citations
... This fi nding underlines the importance of the active screening for dyslipidemia in this group of patients. We found that the level of triglycerides and that of HDL-cholesterol correlated positively and negatively, respectively, with waist circumference -fi ndings confi rmed in previous studies [28,29]. Therefore, it is not surprising that our patient cohort, characterized by lower presence of visceral obesity compared to the general population, had a lower frequency of dyslipidemia, as well. ...
Aim
Our aim was to assess the prevalence of the metabolic syndrome (MetS) and its components in patients with controlled Graves’ disease (GD).
Methods
This was a cross-sectional study involving 95 consecutive patients with GD referred to our tertiary care inpatient clinical center meeting the following inclusion criteria: controlled hyperthyroidism, treatment with antithyroid drugs, untreated Graves’ orbitopathy (GO), if present. Patients’ anthropometric parameters were evaluated and laboratory tests were performed with measurement of fasting blood glucose, total cholesterol, LDL-cholesterol, HDL-cholesterol, triglycerides, thyroid hormone and antibody levels. The presence of the MetS and its components as defined by the International Diabetes Federation from 2009 were evaluated.
Results
In our patient cohort 82.1% were females, 17.9% were males, mean age 50.2 ± 13 years, with median duration of GD 16.5 months. The MetS was observed in 32.6% of our patients, obesity – in 34.7%, hyperglycemia in 38.9%, arterial hypertension – in 36.8%, low HDL-cholesterol – in 23.2% and hypertriglyceridemia – in 13.7%. There was not statistical difference neither between the prevalence of the MetS, nor between the prevalence of its individual components in female and male GD patients. The MetS was significantly more frequent in older patients, as well as abdominal obesity, hyperglycemia and arterial hypertension. There was not statistical difference in the frequency of the MetS and its components between GD patients with and without GO, except for waist circumference, which was significantly higher in patients with GO.
Conclusions
The presence of the MetS and its components among GD patients are to great extent similar to those reported in the general population, which underlines the need for their screening and proper treatment in this subpopulation.
... Since each 3DO body scanner relies on its own algorithms, measurements obtained from different 3DO body scanners cannot directly be combined or compared [43]. The 3DO body scanner VITUS Smart XXL had small but relevant errors, i.e., up to 5 cm for waist circumference [44]. However, the high precision of these devices [45,46], along with performing visual inspection of all scans, supports the consistency of measures for clinical anthropometry. ...
Background and aim: Body shape and anthropometrics are well-known risk factors for
cardiovascular diseases (CVD) and mortality. Hand-grip strength (HGS) is also a meaningful
marker of health and a promising predictor of CVD and mortality. There is a lack of studies that
have systematically investigated associations between body shape and anthropometrics with
HGS. In a population-based study, we investigated if anthropometric markers derived from 3D
body scanning are related to HGS.
Methods and results: We used the data of 1,599 individuals aged 36 to 93 years, who participated in
the Study of Health in Pomerania. A total of 87 anthropometric markers, determined by a 3D body
scanner, were included in the analysis. Anthropometric measurements were standardized and
used as exposure variables. HGS was measured with a hand dynamometer and used as outcome.
Sex-stratified linear regression models adjusted for age and height were used to relate standard-
ized anthropometrics and HGS. Anthropometric markers were ranked according to -log-p-values.
In men, left and right forearm circumference, left arm length to neck (C7), left forearm length,
and forearm-fingertip length were most strongly related to HGS. In women, right forearm circum-
ference, forearm-fingertip length, shoulder breadth, left forearm circumference, and right wrist
circumference showed the most significant associations with HGS. The final prediction models
contained 13 anthropometric markers in males (R2Z0.54) and eight anthropometric markers in
females (R2Z0.37).
Conclusions: The identified parameters may help estimate HGS in the clinical setting. However,
studies in clinical settings are essential to validating our findings.
... Applications range from fashion design to ergonomics and healthcare. The validity and reliability of body scanning technology compared to manual measurements was repeatedly demonstrated [8][9][10][11][12][13][14][15]. ...
... We were able to confirm excellent agreement of tape and body scan measurements obtained in this study cohort, enabling further analyses with data from follow-up examinations. Consistent with other studies, we found that body scan parameters are slightly larger than the corresponding tape measurements [8,9,13,14]. This might be due to the constriction of soft tissue via tape tension or subject behavior, such as holding their breath or pulling in the stomach, during measurements, as previously described [13]. ...
... Consistent with other studies, we found that body scan parameters are slightly larger than the corresponding tape measurements [8,9,13,14]. This might be due to the constriction of soft tissue via tape tension or subject behavior, such as holding their breath or pulling in the stomach, during measurements, as previously described [13]. Body scan measurements might, accordingly, give a better estimate of the true circumference at the examined location. ...
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.
... The device is able to automatically determine more than 150 body measurements like numerous circumferences, linear dimensions, or regional volumes. A number of validation studies has shown the applicability of the scan technique in an epidemiological setting by comparing scans with manual measurements (e.g., waist or hip circumferences) [27][28][29][30]. Good feasibility, reliability and validity of the scans were shown in these studies, and the correlations with parameters linked to metabolic syndrome were comparable to those of studies using manual measurements [28]. ...
... A number of validation studies has shown the applicability of the scan technique in an epidemiological setting by comparing scans with manual measurements (e.g., waist or hip circumferences) [27][28][29][30]. Good feasibility, reliability and validity of the scans were shown in these studies, and the correlations with parameters linked to metabolic syndrome were comparable to those of studies using manual measurements [28]. ...
... Second, an 8-point bioelectrical impedance analysis (BIA) (Seca mBCA 515, Seca AG, Reinach, Switzerland) was utilized to evaluate the total body fat, visceral fat as well as skeletal muscle mass of the participants. The Seca mBCA 515 device has been verified in various studies [36][37][38] and successfully used in other publications that compare 3D body scans with BIA [28,39]. Participants stood on the four foot-electrodes barefoot and put both hands on the four hand electrodes. ...
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.
... Hip circumference was also measured at the point of maximum circumference over the buttocks using a nonelastic meter [13]. Trained nurses measured blood pressure using the standard protocol de ned by the Joint National Committee (JNC-8). ...
Background: Disease-discordant twins are excellent subjects for matched case-control studies since the confounding effects of age, sex, genetic background, intrauterine, and early environment factors are perfectly controlled. We aimed to investigate how genetic and environmental factors influence cardiometabolic risk factors in a sample of twins in Iran. Methods: Past medical history and physical examination were collected for all participants. Fasting venous blood samples were taken to measure fasting blood glucose (FBG) and lipids levels. Descriptive statistical analysis was used to present the characteristics of twin pairs. Bivariate correlations between the same age- and gender-corrected parameters were separately analysed in monozygotic and dizygotic pairs. The ACE model i.e., the additive genetic (A) effects, and common (C), and unique (E) environmental influences on the trait was used to assess heritability as a structural equation model. Results: This cross-sectional study included 710 (210 monozygotic and 500 dizygotic) twin pairs (Range age: 2-52 years) (mean age: 11.67 ± 10.71 years) who enrolled in the Isfahan Twin Registry (ITR) in 2017. In early childhood (2-6 years), shared environmental influenced on height (by 76%), weight (by 75%), and body mass index (BMI) (by73%). In late childhood (7-12 years), hip circumference, waist circumference (WC), and LDL-cholesterol are highly heritable, 90%, 76%, and 64%, respectively. In adolescents, the following risk factors were highly or moderately heritable: height (94%), neck circumference (85%), LDL-cholesterol (81%), WC (70%), triglycerides (69%), weight (68%), and BMI (65%). In adult twins, arm circumference (97%), weight (86%), BMI (82%), and neck circumference (81%) were highly heritable.
Conclusion: In our study, we observed that various factors, both genetic and environmental, exert an impact on individuals at different stages of their lives. Particularly, we found that certain traits, such as obesity, are highly heritable during childhood but their heritability tends to decline as one progresses into adulthood.
... Anthropometric measurements of the human body are applicable to many aspects of human life [1]. Anthropometry is used in scientific research, clinical examinations, and medicine [2][3][4], in dietetics [5], biomechanics [6][7][8], and in the clothing industry [9]. The basis of anthropometry is an anthropometric measurement that requires the application of an appropriate measurement procedure and the use of specialized, sometimes expensive, measuring tools (e.g., anthropometer, measuring tapes, and caliper). ...
... The basis of anthropometry is an anthropometric measurement that requires the application of an appropriate measurement procedure and the use of specialized, sometimes expensive, measuring tools (e.g., anthropometer, measuring tapes, and caliper). In addition, the measurement process is usually complicated, uncomfortable, time-consuming, and requires properly trained personnel [1,2,10,11]. ...
... An alternative to classical anthropometry became imaging methods commonly used in medicine (DXA, CT, MRI) [1], as well as estimation of anthropometric parameters using computer vision [11] and a 3D laser body scanner [12]. According to Jaeschke et al. [2], in order to improve the measurement of human body parameters (length, circumference of the trunk, hips, or other body parts), scanners visualizing a three-dimensional human model may prove useful. Liu et al. [13] stated that 3D scanners have fundamentally changed the approach to this type of anthropometric measurement in recent years. ...
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.
... (2,3) Specifically, both low SES (4,5) and rural occupancy (6) are associated with higher rates of abdominal obesity, which is itself linked to a higher risk of cardiometabolic abnormalities. (7) Traditionally, abdominal obesity is evaluated by standard anthropometric assessments that include circumferences of the waist -and -hips specifically, given their association with cardiometabolic health risks (8,9) and mortality. (10) Nevertheless, traditional anthropometric measures lack feasibility for those without access to clinical care, which is concerning given that there are few alternative methods that can successfully provide remote and cost-effective assessments without a trained technician present. ...
... In our study, all automated anthropometrics produced precision estimates that were similar to the tape measurements performed in our study (which were conducted professionally) and those produced by three-dimensional scanning in others. (9,29) Interestingly, the ME360 Apple application produced better precision estimates than those collected via tape measure with ME360 Samsung only marginally lower. It is possible that these small differences are due to differences in the developmental software (i.e., iOS or Android ® ), where initial mobile applications are built for a specific device (i.e., iPhone ® or Samsung ® ) with operating systems that require a particular coding language. ...
Automated visual anthropometrics produced by mobile applications are accessible and cost-effective with the potential to assess clinically relevant anthropometrics without a trained technician present. Thus, the aim of this study was to evaluate the precision and agreement of smartphone-based automated anthropometrics against reference tape measurements. Waist and hip circumference (WC; HC), waist-to-hip ratio (WHR), and waist-to-height ratio (W:HT), were collected from 115 participants (69 F) using a tape measure and two smartphone applications (MeThreeSixty®, myBVI®) across multiple smartphone types. Precision metrics were used to assess test-retest precision of the automated measures. Agreement between the circumferences produced by each mobile application and the reference were assessed using equivalence testing and other validity metrics. All mobile applications across smartphone types produced reliable estimates for each variable with ICCs ≥0.93 (all p<0.001) and RMS-%CV between 0.5%-2.5%. PE for WC and HC were between 0.5cm-1.9cm. WC, HC, and W:HT estimates produced by each mobile application demonstrated equivalence with the reference tape measurements using 5% equivalence regions. Mean differences via paired t-tests were significant for all variables across each mobile application (all p<0.050) showing slight underestimation for WC and slight overestimation for HC which resulted in a lack of equivalence for WHR compared to the reference tape measure. Overall, the results of our study support the use of WC and HC estimates produced from automated mobile applications, but also demonstrates the importance of accurate automation for WC and HC estimates given their influence on other anthropometric assessments and clinical health markers.
... Previous studies verified the validity of anthropometric measurements using a 3D body scanner 22,23 . Anthropometric markers were measured with a 3D body scanner (VITUS Smart XXL, Vitronic, Wiesbaden, Germany) using the software AnthroScan Professional (Version 3.0.7, ...
The assessment of cardiorespiratory fitness (CRF) is an important tool for prognosis evaluation of cardiovascular events. The gold standard to measure CRF is cardiopulmonary exercise testing (CPET) to determine peak oxygen uptake (VO2peak). However, CPET is not only time consuming but also expensive and is therefore not widely applicable in daily practice. The aim of our study was to analyze, whether and which anthropometric markers derived from a 3D body scanner were related to VO2peak in a general population-based study. We analyzed data (SHIP-START-3) from 3D body scanner and CPET of 1035 subjects (529 women; 51.1%, age range 36–93). A total of 164 anthropometric markers were detected with the 3D body scanner VITUS Smart XXL using the software AnthroScan Professional. Anthropometric measurements were standardized and associated with CRF by sex-stratified linear regression models adjusted for age and height. Anthropometric markers were ranked according to the − log- p values derived from these regression models. In men a greater left and right thigh-knee-ratio, a longer forearm-fingertip length, a greater left thigh circumference and greater left upper arm circumference were most strongly associated with a higher VO2peak. In women a greater left and right thigh circumference, left calf circumference, thigh thickness and right calf circumference were most strongly associated with a higher VO2peak. The detected VO2peak-related anthropometric markers could be helpful in assessing CRF in clinical routine. Commonly used anthropometric markers, e.g. waist and hip circumference, were not among the markers associated with VO2peak.
... During the early days, researchers validated the accuracy and precision of the automated anthropometry to criterion methods (e.g., tape measurements to circumferences/lengths, underwater weighing or ADP to total volume) (15,16). 3DO waist circumference, hip circumference, and waist-hip-ratio were highly associated to metabolic markers and improved predictions for metabolic syndrome (17,18). Researchers also showed that these automated anthropometric estimates, where some would be difficult and tedious to obtain manually, were predictive of DXA FM and FFM (19-22). ...
Background: Recent three-dimensional optical (3DO) imaging advancements have provided a more accessible, affordable, and self–operating opportunities for assessing body composition. 3DO is accurate and precise compared to clinical measures measured by dual–energy X–ray absorptiometry (DXA) in diverse study samples. However, the accuracy and precision of an overall 3DO body composition model in specific subgroups is unknown. Therefore, this study aimed to evaluate 3DOs accuracy and precision by subgroups of age, body mass index (BMI), and ethnicity/race.
Methods: A cross–sectional analysis was performed using the Shape Up! Adults study. Each participant received duplicate 3DO and DXA scans. 3DO meshes were digitally registered and reposed using Meshcapade to standardize the vertices and pose. Principal component analysis was performed on the registered 3DO meshes to orthogonalize and reduce the dimensionality of the data. The resulting principal components estimated DXA whole–body and regional body composition using stepwise forward linear regression with five–fold cross–validation. Duplicate 3DO and DXA scans were used for test–retest precision. Student t–test was performed between 3DO and DXA by subgroup to determine significant differences. One–way ANOVA determined if intra–group precision had significant differences. P–value < 0.05 was considered statistically significant.
Results: Six hundred thirty–four participants (females = 346) had completed the study at the time of the analysis. 3DO total fat mass (FM) and fat–free mass (FFM) in the entire sample achieved R2s of 0.94 and 0.92 with RMSEs of 2.91 kg and 2.76 kg, respectively, in females and similarly in males. 3DO total FM and FFM achieved a %CV (RMSE) of 1.76% (0.44 kg) and 1.97% (0.44 kg), while DXA had a %CV (RMSE) of 0.98% (0.24 kg) and 0.59% (0.27 kg), respectively, in females and similarly in males. There were no mean differences by age group (p–value > 0.068). However, there were mean differences for underweight females, NHOPI females and males, and Asian and black females (p–value < 0.038). There were no significant differences among the subgroups for precision (p–value > 0.109).
Conclusion: A single 3DO body composition model derived from a highly–stratified dataset performed well against DXA with minimal differences detected for accuracy and precision. Adjustments to specific subgroups may be warranted to improve the accuracy in those that had significant differences. Nevertheless, 3DO produced accurate and precise body composition estimates that can be used on diverse populations.
... According to Size Stream (MeThreeSixty) waist landmarking is defined as "horizontal contour circumference taken at the narrowest torso width between the chest and hips when viewed from the front". Moreover, there are four parameters of waist circumference such as waist girth, high waist girth, waist band and belly circumference [23]. Each landmarking definition of waist circumference shows variability 3D look provided definition does not define that exact waist level and Size Stream pointed out narrowest torso. ...
... The width of the feet needs to be selected universally for body scanners and then its differences can be identified accordingly. Jaeschke, Steinbrecher and Pischon (2015) presents five parameters of hip circumference for instance buttockgirth, middle hip, high hip girth, hip girth and hip thigh girth [23]. The landmarking definitions can also be evaluated, the Size Stream defined landmarking of hip circumference as "Maximum contour horizontal circumference found between the height of the Back Waist landmark and Crotch landmark by size stream". ...
Abstract
The clothing industry around the globe frequently use human body measurements for garment production. This study aims to determine the potential of 3D body scanning feature of mobile application for product development and selection of right size and fitted garment using fashion e-commerce platform. Digital measurement methods have been introduced recently and developed extensively replacing the traditional manual measurement techniques. The paper addresses to determine the practicability of digital measurements acquired from 3D body mobile scanners in terms of reliability and validity. Formerly, for size and fit recommendation and visualisation, using technology driven interfaces user interaction was approached in terms of receiving body size and shape information manually as well as past purchase history of a garment [1]. However, recently the web 3.0 metaverse fashion technology feature such as 3D body mobile scanners have the potential to enhance the fashion virtual size and fit e-commerce platform for online apparel shopping. Therefore, 3D mobile scanners would be helpful to enrich the accuracy of garment size and fit prediction and garment construction for online shoppers without using user’s manual information input in the interface. An exploratory quantitative study has been conducted. The two mobile application scanners (3D Look and MeThreeSixty) have been studied for this paper [2] [3]. The digital body measurements have been analysed comparatively to determine the difference of body measurements extracted from both applications for each participant. Reliability comparison have been estimated in terms of standard error of mean measurement (SEM) to ANSUR allowable errors [4]. Validity was analysed according to ISO 20685 [5]. The reliability of 3D body scanning technologies has been evidenced in various studies [4][6] [7][8] [9]. The Pakistani female, age 18-65+ years has been recruited to participate in the study. The data has been collected by self-scanning method using their own smartphones at home [2] [3]. The mobile applications are available free for users on both Android and iOS.
Keywords: Mobile app scanners, Fashion e-commerce, 3D body scanning
