Surface Anthropometry Research Articles

Practical Computer Vision Application to Compute Total Body Surface Area Burn

Critical burn management decisions rely on accurate percent total body surface area (%TBSA) burn estimation. Existing %TBSA burn estimation models (eg, Lund-Browder chart and rule of nines) were derived from a linear formula and a limited number of individuals a century ago and do not reflect the range of body habitus of the modern population. To develop a practical %TBSA burn estimation tool that accounts for exact burn injury pattern, sex, and body habitus. This population-based cohort study evaluated the efficacy of a computer vision algorithm application in processing an adult laser body scan data set. High-resolution surface anthropometry laser body scans of 3047 North American and European adults aged 18 to 65 years from the Civilian American and European Surface Anthropometry Resource data set (1998-2001) were included. Of these, 1517 participants (49.8%) were male. Race and ethnicity data were not available for analysis. Analyses were conducted in 2020. The contributory %TBSA for 18 body regions in each individual. Mobile application for real-time %TBSA burn computation based on sex, habitus, and exact burn injury pattern. Of the 3047 individuals aged 18 to 65 years for whom body scans were available, 1517 (49.8%) were male. Wide individual variability was found in the extent to which major body regions contributed to %TBSA, especially in the torso and legs. Anterior torso %TBSA increased with increasing body habitus (mean [SD], 15.1 [0.9] to 19.1 [2.0] for male individuals; 15.1 [0.8] to 18.0 [1.7] for female individuals). This increase was attributable to increase in abdomen %TBSA (mean [SD], 5.3 [0.7] to 8.7 [1.8]) among male individuals and increase in abdomen (mean [SD], 4.6 [0.6] to 6.8 [1.7]) and pelvis (mean [SD], 1.5 [0.2] to 2.9 [0.9]) %TBSAs among female individuals. For most body regions, Lund-Browder chart and rule of nines estimates fell outside the population's measured interquartile ranges. The mobile application tested in this study, Burn Area, facilitated accurate %TBSA burn computation based on exact burn injury pattern for 10 sex and body habitus-specific models. Computer vision algorithm application to a large laser body scan data set may provide a practical tool that facilitates accurate %TBSA burn computation in the modern era.

Facial Surface Anthropometric Features and Measurements With an Emphasis on Rhinoplasty.

Facial features and measurements are utilized to analyze patients' faces for various reasons, including surgical planning, scientific communications, patient-surgeon communications, and post-surgery evaluations. There are numerous descriptions regarding these features and measurements scattered throughout the literature, and the authors did not encounter a current compilation of these parameters in the medical literature. A narrative literature review of the published medical literature for facial measurements used for facial analysis in rhinoplasty was conducted through the electronic databases MEDLINE/PubMed and Google Scholar, along with a citation search. A total of 61 facial features were identified: 45 points (25 bilateral, 20 unilateral), 5 lines (3 bilateral, 2 unilateral), 8 planes, and 3 areas.A total of 122 measurements were identified: 48 distances (6 bilateral, 42 unilateral), 57 angles (13 bilateral, 44 unilateral), and 17 ratios. Supplemental figures were created to depict all features and measurements utilizing a frontal, lateral, or basal view of the face. This paper provides the most comprehensive and current compilation of facial measurements to date. The authors believe this compilation will guide further developments (methodologies and software tools) for analyzing nasal structures and assessing the objective outcomes of facial surgeries, in particular rhinoplasty. Moreover, it will improve communication as a reference for facial measurements of facial surface anthropometry, in particular rhinoplasty.

Short-Term Precision Error of Body Composition Assessment Methods in Resistance-Trained Male Athletes.

Athletic populations require high-precision body composition assessments to identify true change. Least significant change determines technical error via same-day consecutive tests but does not integrate biological variation, which is more relevant for longitudinal monitoring. The aim of this study was to assess biological variation using least significant change measures from body composition methods used on athletes, including surface anthropometry (SA), air displacement plethysmography (BOD POD), dual-energy X-ray absorptiometry (DXA), and bioelectrical impedance spectroscopy (BIS). Thirty-two athletic males (age = 31 ± 7years; stature = 183 ± 7cm; mass = 92 ± 10kg) underwent three testing sessions over 2 days using four methods. Least significant change values were calculated from differences in Day 1 Test 1 versus Day 1 Test 2 (same-day precision), as well as Day 1 Test 1 versus Day 2 (consecutive-day precision). There was high agreement between same-day and consecutive-day fat mass and fat-free mass measurements for all methods. Consecutive-day precision error in comparison with the same-day precision error was 50% higher for fat mass estimates from BIS (3,607 vs. 2,331g), 25% higher from BOD POD (1,943 vs. 1,448g) and DXA (1,615 vs. 1,204g), but negligible from SA (442 vs. 586g). Consecutive-day precision error for fat-free mass was 50% higher from BIS (3,966 vs. 2,276g) and SA (1,159 vs. 568g) and 25% higher from BOD POD (1,894 vs. 1,450g) and DXA (1,967 vs. 1,461g) than the same-day precision error. Precision error in consecutive-day analysis considers both technical error and biological variation, enhancing the identification of small, yet significant changes in body composition of resistance-trained male athletes. Given that change in physique is likely to be small in this population, the use of DXA, BOD POD, or SA is recommended.

Development of an Anthropometric Prediction Model for Fat-Free Mass and Muscle Mass in Elite Athletes

The monitoring of body composition is common in sports given the association with performance. Surface anthropometry is often preferred when monitoring changes for its convenience, practicality, and portability. However, anthropometry does not provide valid estimates of absolute lean tissue in elite athletes. The aim of this investigation was to develop anthropometric models for estimating fat-free mass (FFM) and skeletal muscle mass (SMM) using an accepted reference physique assessment technique. Sixty-four athletes across 18 sports underwent surface anthropometry and dual-energy X-ray absorptiometry (DXA) assessment. Anthropometric models for estimating FFM and SMM were developed using forward selection multiple linear regression analysis and contrasted against previously developed equations. Most anthropometric models under review performed poorly compared with DXA. However, models derived from athletic populations such as the Withers equation demonstrated a stronger correlation with DXA estimates of FFM (r = .98). Equations that incorporated skinfolds with limb girths were more effective at explaining the variance in DXA estimates of lean tissue (Sesbreno FFM [R2 = .94] and Lee SMM [R2 = .94] models). The Sesbreno equation could be useful for estimating absolute indices of lean tissue across a range of physiques if an accepted option like DXA is inaccessible. Future work should explore the validity of the Sesbreno model across a broader range of physiques common to athletic populations.

Differences in visceral adipose tissue and biochemical cardiometabolic risk markers in elite rugby union athletes of Caucasian and Polynesian descent

Polynesian individuals are leaner with greater musculature than Caucasians of an equivalent size, and this genetically different morphology provides a physique that is often compatible with success in a number of sports, including rugby union. Evidence indicates that Polynesians have greater stores of absolute and relative abdominal fat mass and this is known to confer cardiometabolic risk. The aims of this study were to (1) explore the relationship between ethnicity, visceral adipose tissue (VAT), and cardiometabolic disease risk markers in elite Caucasian and Polynesian rugby union athletes, and (2) assess the impact of a pre-season training programme on these markers. Twenty-two professional rugby union athletes of Caucasian (n = 11) and Polynesian (n = 11) descent underwent physique assessment via surface anthropometry, dual-energy X-ray absorptiometry, and magnetic resonance imaging before and after an 11-week pre-season. A fasted blood test was undertaken at both time points. Compared to Caucasians, at baseline Polynesians displayed significantly higher VAT (771 ± 609 cm3 vs 424 ± 235 cm3; p = 0.043), triglycerides (1.0 ± 0.9 mmol/L vs 0.6 ± 0.2 mmol/L; p = 0.050), and low-density lipoprotein cholesterol (3.1 ± 0.9 mmol/L vs 2.3 ± 0.7 mmol/L; p = 0.019). Similar changes were observed in both groups over the pre-season period in VAT and blood biochemical markers. Polynesian rugby union athletes were more likely than Caucasians to exhibit risk factors associated with cardiometabolic disease, such as elevated VAT and unfavourable lipid profiles. Further longitudinal research is required to identify and explain the short- and long-term risk of cardiometabolic disease in athletes of Polynesian descent.

Longitudinal Changes in Body Composition Assessed Using DXA and Surface Anthropometry Show Good Agreement in Elite Rugby Union Athletes.

Rugby union athletes have divergent body composition based on the demands of their on-field playing position and ethnicity. With an established association between physique traits and positional requirements, body composition assessment is routinely undertaken. Surface anthropometry and dual-energy X-ray absorptiometry (DXA) are the most common assessment techniques used, often undertaken synchronously. This study aims to investigate the association between DXA and surface anthropometry when assessing longitudinal changes in fat-free mass (FFM) and fat mass (FM) in rugby union athletes. Thirty-nine elite male rugby union athletes (age: 25.7 ± 3.1years, stature: 187.6 ± 7.7cm, and mass: 104.1 ± 12.2kg) underwent assessment via DXA and surface anthropometry multiple times over three consecutive international seasons. Changes in the lean mass index, an empirical measure to assess proportional variation in FFM, showed large agreement with changes in DXA FFM (r = .54, standard error of the estimate = 1.5%, p < .001); the strength of association was stronger among forwards (r = .63) compared with backs (r = .38). Changes in the sum of seven skinfolds showed very large agreement with changes in DXA FM (r = .73, standard error of the estimate = 5.8%, p < .001), with meaningful differences observed regardless of ethnicity (Whites: r = .75 and Polynesians: r = .62). The lean mass index and sum of seven skinfolds were able to predict the direction of change in FFM and FM 86% and 91% of the time, respectively, when DXA change was >1kg. Surface anthropometry measures provide a robust indication of the direction of change in FFM and FM, although caution may need to be applied when interpreting magnitude of change, particularly with FM.

Walking balance on a treadmill changes during pregnancy

BackgroundAltered standing balance during pregnancy has been previously reported. To date, body center of mass (bCOM) motion has not been used to track balance changes in this population. We recently compared three methods to determine the torso center of mass (tCOM) location (via force plate acquired center of pressure calculation, using Pavol surface anthropometry measurements, and a combination of the two) to use in calculating the bCOM during pregnancy. Research questionThis current research explored two questions: (1) does walking balance change during pregnancy, and (2) do the methods for identifying tCOM location affect the resulting balance measures? MethodsFifteen pregnant women were recruited to perform 60-second trial of treadmill walking at 4-week intervals from 12 weeks gestation until delivery. Walking balance was measured as bCOM motion within the base of support. Gestation time and anthropometric model (force plate, Pavol, and combination) were repeated-measures independent variables in a general linear mixed model analysis. ResultsThere was a significant decrease in walking balance during pregnancy. As gestation progressed, we observed non-linear changes in the bCOM motion within the base of support over time, with some changes starting early in pregnancy and others not starting until late 2nd trimester. The anthropometric model used to locate the bCOM significantly influences balance measures. The results of this study indicate that the force plate method is more appropriate for locating the tCOM in the anterior and lateral directions. SignificanceThe results of this study will inform clinicians and patients about the gestational stage-associated changes in balance during pregnancy that increase the risk of falling and injury. Researchers should also carefully consider the method for locating the bCOM.

Influence of subject presentation on interpretation of body composition change after 6months of self-selected training and diet in athletic males.

High precision body composition assessment methods accurately monitor physique traits in athletes. The acute impact of subject presentation (ad libitum food and fluid intake plus physical activity) on body composition estimation using field and laboratory methods has been quantified, but the impact on interpretation of longitudinal change is unknown. This study evaluated the impact of athlete presentation (standardised versus non-standardised) on interpretation of change in physique traits over time. Thirty athletic males (31.2 ± 7.5 years; 182.2 ± 6.5cm; 91.7 ± 10.3kg; 27.6 ± 2.6kg/m2) underwent two testing sessions on 1day including surface anthropometry, dual-energy X-ray absorptiometry (DXA), bioelectrical impedance spectroscopy (BIS) and air displacement plethysmography (via the BOD POD), with combinations of these used to establish three-compartment (3C) and four-compartment (4C) models. Tests were conducted after an overnight fast (BASEam) and ~ 7h later after ad libitum food/fluid and physical activity (BASEpm). This procedure was repeated 6months later (POSTam and POSTpm). Magnitude of changes in the mean was assessed by standardisation. After 6months of self-selected training and diet, standardised presentation testing (BASEam to POSTam) identified trivial changes from the smallest worthwhile effect (SWE) in fat-free mass (FFM) and fat mass (FM) for all methods except for BIS (FM) where there was a large change (7.2%) from the SWE. Non-standardised follow-up testing (BASEam to POSTpm) showed trivial changes from the SWE except for small changes in FFM (BOD POD) of 1.1%, and in FM (3C and 4C models) of 6.4 and 3.5%. Large changes from the SWE were found in FFM (BIS, 3C and 4C models) of 2.2, 1.8 and 1.8% and in FM (BIS) of 6.4%. Non-standardised presentation testing (BASEpm to POSTpm) identified trivial changes from the SWE in FFM except for BIS which was small (1.1%). A moderate change from the SWE was found for BOD POD (3.3%) and large for BIS (9.4%) in FM estimations. Changes in body composition utilising non-standardised presentation were more substantial and often in the opposite direction to those identified using standardised presentation, causing misinterpretation of change in physique traits. Standardised presentation prior to body composition assessment for athletic populations should be advocated to enhance interpretation of true change.

A 3D anthropometric sizing analysis system based on North American CAESAR 3D scan data for design of head wearable products

Abstract The present study developed a sizing analysis system for head-related product designs based on the Civilian American and European Surface Anthropometry Resource (CAESAR) database of North Americans. A total of 2299 heads in the CAESAR database were manually edited and 26 anthropometric landmarks were marked on the edited 3D heads to measure 30 anthropometric dimensions related to head-related product designs. The 3D anthropometric sizing analysis system (3D-ASAS) developed in the study provides analysis functions of a sizing system and representative face models by considering a target product, a target population, the number of size categories, and key anthropometric dimensions based on the CAESAR head measurements. Further research to reduce the efforts of manual editing and landmarking of 3D body scan data is discussed for efficient application of the 3D-ASAS to the design process of various wearable products.

Female breast shape categorization based on analysis of CAESAR 3D body scan data

In this study we explore the variation in female breast shape across the younger (age: 18–45), non-obese (BMI &lt; 30) North American Caucasian population, a population that has not previously been well-represented in studies of breast shape. A method of classifying breast shape was developed based on multiple data-mining techniques. Forty-one relative measurements (i.e., ratios and angles) were constructed from 66 raw measurements (circumferences, depths, widths, etc.), extracted from 478 CAESAR (Civilian American and European Surface Anthropometry Resource) scans, using self-developed Matlab® programs. Seventy subjects were regarded as outliers and were removed. The remaining data were transformed and standardized to ensure robust analysis. To judge results, an algorithm was developed to visualize clustering outcomes in the form of side profiles of breasts. The results of three clustering methods, namely hierarchical, K-means, and K-medoids clustering, were compared. Finally, breast shapes were categorized into three and five groups by two different cluster number selection criteria proposed by the study: (1) based on misclassification rate; (2) based on the goodness-of-fit of the model. Several of the relative body measurements were identified to be critical in defining breast shape. The findings and the proposed methods of this study can contribute to the development of improved shape and sizing systems of bra products that work for both manufacturers and consumers. The new methodology developed in this study can also be applied to other types of intimate apparel products where an understanding of body shape plays a key role in body support, comfort, and fit.

Factors affecting occlusion pressure and ischemic preconditioning

Purpose: To determine the effect of limb selection (upper/lower), cuff width (small (6 cm)/medium (13 cm) upper; medium/large (18 cm) lower) and anthropometry on arterial occlusion pressure (AOP) in ischemic preconditioning (IPC). Methods: Twenty athletes (10 females and 10 males) had surface anthropometry and dual x-ray absorptiometry (DXA) assessments before using Doppler ultrasound to confirm AOP for each limb. Subsequently, 5 min of occlusion occurred, with near-infrared spectroscopy (NIRS) measuring muscle oxygenation changes. Resultant AOP was compared between sexes, limbs and cuff sizes using linear regression models. Results: Mean AOP was higher in the lower limbs than the upper limbs (161 ± 18 vs. 133 ± 12 mm Hg; p < .001), and with smaller cuffs in upper (161 ± 16 vs. 133 ± 12 mm Hg; p < .001), but not lower limbs (161 ± 16 vs. 170 ± 26 mm Hg; p = .222). Sex and resting systolic blood pressure (SBP) accounted for 77% (small cuff) to 83% (medium cuff) of variance in AOP for upper limbs, and 61% (medium cuff) to 63% (large cuff) in lower limbs. Including anthropometry accounted for 82% (small cuff) to 89% (medium cuff) and 78% (medium cuff) to 79% (large cuff) of variance for upper and lower limbs, respectively. Adding DXA variables improved the explained variance up to 83% (small cuff) to 91% (medium cuff) and 79% (medium cuff) to 87% (large cuff) for upper and lower limbs, respectively. NIRS data showed significantly greater tissue oxygenation changes in upper versus lower limbs. Conclusions: The AOP in athletes is dependent on limb occluded, sex, SBP, limb and cuff size, and body composition.

An overview of methods to assess body composition

Scientific advancement has led to new technologies in the field of body composition assessment. Surface anthropometry has traditionally been used to assess body composition through the internationally recognised methodology of the International Society for the Advancement of Kinanthropometry (ISAK). However, the commercialisation of devices providing bioelectrical impedance analysis, dual energy X-ray absorptiometry, magnetic resonance imaging, three-dimensional photonic scanning (3DS), air-displacement plethysmography (i.e. Bod Pod), ultrasound techniques and dilution techniques (doubly-labelled water), has led to the adoption of new and often non-standardised, measurement techniques. Practitioners, all over the world, are employing these new technologies to measure and monitor change in body size, shape and composition for the purposes of health management, talent identification and development, optimising physique for sport performance, and enabling sports equipment design and fit. The accuracy and reliability of the technique measures are critical in a field where tracking small changes in an athlete's physique is important. When athletes have their body composition measured across multiple technologies in a non-standardised manner, they often receive varying results which can be confusing and, in some cases, distressing. Currently, no reference or model exists for the standardisation of many of these new devices. There is a lack of awareness of standardisation of technique among both manufacturers & practitioners. There is often a lack of established protocols to ensure best practice in physique assessment. Different protocols can make large differences to the measurement value when they purport to measure the same thing – e.g. waist girth (up to 12% in females); Breathing cycle in 3D scan-derived % fat (15% for end tidal, rising to 28% on inspiration and reducing to 10% in expiration). These two examples underscore the importance of standardising protocols for body composition assessment. This presentation will outline considerations for current best practice to assess body composition. Examples for physique assessment in clinical practice using a selection of the technologies will be provided from the international team of co-authors in the Best Practice Protocols for Physique Assessment in Sport book (to be published by Springer International, November 2017).

Skinfold Prediction Equations Fail to Provide an Accurate Estimate of Body Composition in Elite Rugby Union Athletes of Caucasian and Polynesian Ethnicity.

Body composition in elite rugby union athletes is routinely assessed using surface anthropometry, which can be utilized to provide estimates of absolute body composition using regression equations. This study aims to assess the ability of available skinfold equations to estimate body composition in elite rugby union athletes who have unique physique traits and divergent ethnicity. The development of sport-specific and ethnicity-sensitive equations was also pursued. Forty-three male international Australian rugby union athletes of Caucasian and Polynesian descent underwent surface anthropometry and dual-energy X-ray absorptiometry (DXA) assessment. Body fat percent (BF%) was estimated using five previously developed equations and compared to DXA measures. Novel sport and ethnicity-sensitive prediction equations were developed using forward selection multiple regression analysis. Existing skinfold equations provided unsatisfactory estimates of BF% in elite rugby union athletes, with all equations demonstrating a 95% prediction interval in excess of 5%. The equations tended to underestimate BF% at low levels of adiposity, whilst overestimating BF% at higher levels of adiposity, regardless of ethnicity. The novel equations created explained a similar amount of variance to those previously developed (Caucasians 75%, Polynesians 90%). The use of skinfold equations, including the created equations, cannot be supported to estimate absolute body composition. Until a population-specific equation is established that can be validated to precisely estimate body composition, it is advocated to use a proven method, such as DXA, when absolute measures of lean and fat mass are desired, and raw anthropometry data routinely to derive an estimate of body composition change.

Validation of a new three-dimensional imaging system using comparative craniofacial anthropometry

BackgroundThe aim of this study is to validate a new three-dimensional craniofacial stereophotogrammetry imaging system (3dMDface) through comparison with manual facial surface anthropometry. The null hypothesis was that there is no difference between craniofacial measurements using anthropometry vs. the 3dMDface system.MethodsFacial images using the new 3dMDface system were taken from six randomly selected subjects, sitting in natural head position, on six separate occasions each 1 week apart, repeated twice at each sitting. Exclusion criteria were excess facial hair, facial piercings and undergoing current dentofacial treatment. 3dMDvultus software allowed facial landmarks to be marked and measurements recorded. The same measurements were taken using manual anthropometry, using soluble eyeliner to pinpoint landmarks, and sliding and spreading callipers and measuring tape to measure distances. The setting for the investigation was a dental teaching hospital and regional (secondary and tertiary care) cleft centre. The main outcome measure was comparison of the craniofacial measurements using the two aforementioned techniques.ResultsThe results showed good agreement between craniofacial measurements using the 3dMDface system compared with manual anthropometry. For all measurements, except chin height and labial fissure width, there was a greater variability with the manual method compared to 3D assessment. Overall, there was a significantly greater variability in manual compared with 3D assessments (p < 0.02).ConclusionsThe 3dMDface system is validated for craniofacial measurements.

Anthropometry model generation based on ANSUR II database

This paper presents a three-dimensional (3D) anthropometry model generation (AMG) software framework based on the latest US Army Anthropometric Survey (ANSUR II) database. The software utilises principal component shapes derived from 3D body scans in the database and employs two complementary methods (feature analysis method and database method) to generate 3D surface models directly from anthropometric feature specifications. Virtual landmarks and 3D features identified on the surface models are the keys for success of the present approaches. It is demonstrated that the features calculated from these models are in good agreement with traditional tape or caliper measurements with a few exceptions due to measurement methodology or posture. Besides surface anthropometry, the software is able to construct a dynamic joint segment framework from any of the models and morph associated bones, muscles, interior organs, and clothing accordingly. This AMG software is a valuable tool for AMG in digital human/warfighter/patient modelling for various applications in biomechanics, human factors or ergonomics, physiology, and medicine.

Development of HeadForms and an Anthropometric Sizing Analysis System for Head-Related Product Designs

The present study developed a sizing analysis system based on the Civilian American and European Surface Anthropometry Resource (CAESAR) database of North Americans ( n = 2,299) for head-related product designs. To find representative heads from a huge amount of 3D human scan database, a sizing analysis system is required for efficient analysis of sizing systems based on anthropometric measurements. The head of the CAESAR 3D scan were manually edited to improve a quality for better use to the product design. Twenty one anthropometric landmarks were marked on the edited 3D heads to measure 40 anthropometric dimensions related to the head product designs. All head and face dimensions were automatically measured by applying a measurement system coded using Matlab. Fifteen representative headforms were generated in terms of 5 ethnic groups (composite group, Caucasians, American Africans, Asians, and Hispanics) and 3 gender groups (composite gender, males, and females). Finally, the sizing analysis system was developed based on the measurement of the CAESAR for analysis of head and facial measurements and generation of sizing systems.

Anthropometric Characteristic, Body Composition and Somatotype of Canadian Female Soccer Players

Canadian female junior soccer players were evaluated for their anthropometrical characteristics including somatotype and body composition with a aim to evaluate with their international counterparts. 18 female soccer players with an average age of 16(±0.5) of a local club were assessed during their peak season time . Somatotype was assessed using Heath-Carter method and body composition ( Fat%) was assessed by surface anthropometry . Endomorphic mesomorph (3.0 ±0.8 ─ 3.9±0.8 ─2.58±1.0 ) body type was observed in average with an average 22.1(±3.1) % body fat. Average waist-hip ratio was 0.7 (±0.03) . Though BMI does not reflect the obesity precisely in athletic population, average BMI of the female soccer group was in normal range with an average value of 21.5 (±1.8) kg.m-2 .Thus the Canadian junior female soccer players possessed an average muscularity with slightly higher fat % compare to national level female athletes . The group needed more muscularity with less fattiness.

Functional 3D Human Model Design: A Pilot Study Based on Surface Anthropometry and Infrared Thermography

ABSTRACTWith the rapid development of functional product design, the digital human body applied to design and manufacturing need be improved with more information of the human body. Functional and smart clothing has been a popular trend among consumers. The human model or mannequin may not fully satisfied the increasing demands of anatomical and physiologic messages from the human body in a visual and accurate way. As one of the most important functions of clothing, thermal comfort plays a vital role in many functional clothing design. In this pilot study, a thermal model was introduced to lay a foundation for functional thermal clothing development. A step by step method was commentated to draw a map for functional model development. This model was constructed by geometric human model from 3D scanning data and 2D thermograms from IR camera. The skin temperature data of subject was transferred to exact 3D human body, the temperature distribution and features can be clarified easily for design and manufact...

Body composition characteristics of elite Australian rugby union athletes according to playing position and ethnicity

This study describes the body composition traits of modern-day elite rugby union athletes according to playing position and ethnicity. Thirty-seven international Australian rugby athletes of Caucasian and Polynesian descent undertook body composition assessment using dual-energy X-ray absorptiometry and surface anthropometry. Forwards were significantly taller, heavier and had a greater total fat mass and lean mass than backs. Backs displayed a higher percentage lean mass and lower sum of seven skinfolds and percentage fat mass. While no whole body composition differences were seen between ethnicities, significant regional differences were observed. In the periphery (arm and leg) regions, Polynesians had a greater proportion of fat mass (53.1% vs. 51.3%, P = 0.052, d = 0.5) and lean mass (49.7% vs. 48.6%, P = 0.040, d = 0.9), while in the trunk region a lower proportion of fat mass (37.2% vs. 39.5%, P = 0.019, d = 0.7) and lean mass (45.6% vs. 46.8%, P = 0.020, d = 1.1). Significant differences were also seen between Caucasian and Polynesian forwards in leg lean mass (31.4 kg vs. 35.9 kg, P = 0.014, d = 2.4) and periphery lean mass (43.8 kg vs. 49.6 kg, P = 0.022, d = 2.4). Elite Polynesian rugby athletes have different distribution patterns of fat mass and lean mass compared to Caucasians, which may influence their suitability for particular positions.

Anthropometric Characteristic, Somatotype and Body Composition of Canadian Female Rowers

Canadian female rowers were evaluated for their anthropometrical characteristics including somatotype and body composition to evaluate them with their international counterparts. 31 female rowers with an average age of 28.6 ±3.4 ( range 19-33) yr of different local clubs were assessed during their peak season time. Part of the measurements were done during the fulfilment of assignment for ISAK Kianthropometry accreditation course in Canada and part of the measurements were done during the fitness assessment of rowers at local clubs. Somatotype was assessed using Heath- Carter method and body composition (Fat%) was assessed by surface anthropometry. Endomorphic mesomorph (3.1±0.5 ─4.1±0.6 ─2.3±0.7 ) body type was observed in average with an average 23.4(±2.9) % body fat. Average waist-hip ratio was 0.74 (±0.4) .Canadian female rowers of the present study possessed more than average muscularity with slightly higher body fat % . The present study recommended more muscularity with less body fat % for the Canadian female rowers. The study also recommended a change in body type from endomorphic mesomorph to ectomorphic mesomoeph.