Effect of inaccuracies in anthropometric data and linked-segment inverse dynamic modeling on kinetics of gait in persons with partial foot amputation

The accuracy of data derived from linked-segment models depends on how well the system has been represented. Previous investigations describing the gait of persons with partial foot amputation did not account for the unique anthropometry of the residuum or the inclusion of a prosthesis and footwear in the model and, as such, are likely to have underestimated the magnitude of the peak joint moments and powers. This investigation determined the effect of inaccuracies in the anthropometric input data on the kinetics of gait. Toward this end, a geometric model was developed and validated to estimate body segment parameters of various intact and partial feet. These data were then incorporated into customized linked-segment models, and the kinetic data were compared with that obtained from conventional models. Results indicate that accurate modeling increased the magnitude of the peak hip and knee joint moments and powers during terminal swing. Conventional inverse dynamic models are sufficiently accurate for research questions relating to stance phase. More accurate models that account for the anthropometry of the residuum, prosthesis, and footwear better reflect the work of the hip extensors and knee flexors to decelerate the limb during terminal swing phase.

Obesity screening for young Japanese males and females using skin fold measurements : the classification revisited

Anthropometric assessment is a simple, safe, and cost-efficient method to examine the health status of individu-als. The Japanese obesity classification based on the sum of two skin folds (Σ2SF) was proposed nearly 40 years ago therefore its applicability to Japanese living today is unknown. The current study aimed to determine Σ2SF cut-off values that correspond to percent body fat (%BF) and BMI values using two datasets from young Japa-nese adults (233 males and 139 females). Using regression analysis, Σ2SF and height-corrected Σ2SF (HtΣ2SF) values that correspond to %BF of 20, 25, and 30% for males and 30, 35, and 40% for females were determined. In addition, cut-off values of both Σ2SF and HtΣ2SF that correspond to BMI values of 23 kg/m2, 25 kg/m2 and 30 kg/m2 were determined. In comparison with the original Σ2SF values, the proposed values are smaller by about 10 mm at maximum. The proposed values show an improvement in sensitivity from about 25% to above 90% to identify individuals with ≥20% body fat in males and ≥30% body fat in females with high specificity of about 95% in both genders. The results indicate that the original Σ2SF cut-off values to screen obese individuals cannot be applied to young Japanese adults living today and modification is required. Application of the pro-posed values may assist screening in the clinical setting.

Changes in resting and walking energy expenditure and walking speed during pregnancy in obese women

Background Energy conserving processes reported in undernourished women during pregnancy are a recognised strategy to provide energy required to support fetal development. Women who are obese before conceiving arguably have sufficient fat stores to support the energy demands of pregnancy without the need to provoke energy conserving mechanisms. Objective We tested the hypothesis that obese women would demonstrate behavioural adaptation (i.e. decrease in self-selected walking (SSW) speed) but not metabolic compensation (i.e. decrease in resting metabolic rate (RMR) or metabolic cost of walking) during gestation. Design RMR, SSW speed, metabolic cost of walking, and anthropometry were measured in 23 women (BMI: 33.6 ± 2.5 kg/m2; 31 ± 4 years) at approximately weeks 15 (wk 15) and 30 (wk 30) of gestation. RMR was also measured in two cohorts of non-pregnant controls matched for age, weight and height of the pregnant cohort at wk 15 (N=23) and wk 30 (N=23). Results GWG varied widely (11.3 ± 5.4 kg) and 52% of women gained more weight than is recommended. RMR increased significantly by an average 177 ± 176 kcal/d (11±12%; P<0.0001); however the within-group variability was large. Both the metabolic cost of walking and SSW speed decreased significantly (P<0.01). While RMR increased in >80% of the cohort, the net oxygen cost of walking decreased in the same proportion of women. Conclusions While the increase in RMR was greater than was explained by weight gain, there was evidence of both behavioural and biological compensation in the metabolic cost of walking in obese women during gestation.

How do our 'quicks' generate pace? A cross sectional analysis of the Cricket Australia pace pathway

Technique and physical contributions to ball delivery speed in fast bowling have been popular research topics in sports science. However, a common limiting factor of this work is the level of expertise of participants and lack of within bowler investigations (Salter et al., 2007). The relationship between technique, anthropometry and ball speed has not been comprehensively investigated among elite fast bowlers. The purpose of this study was to examine the relationship between technique, anthropometric variables and ball speed using both within- and betweenbowler analyses in a cross section of the Cricket Australia high performance pace pathway.

Malnutrition and clinical outcomes in elderly patients from a Singapore acute hospital

Older adults, especially those acutely ill, are vulnerable to developing malnutrition due to a range of risk factors. The high prevalence and extensive consequences of malnutrition in hospitalised older adults have been reported extensively. However, there are few well-designed longitudinal studies that report the independent relationship between malnutrition and clinical outcomes after adjustment for a wide range of covariates. Acutely ill older adults are exceptionally prone to nutritional decline during hospitalisation, but few reports have studied this change and impact on clinical outcomes. In the rapidly ageing Singapore population, all this evidence is lacking, and the characteristics associated with the risk of malnutrition are also not well-documented. Despite the evidence on malnutrition prevalence, it is often under-recognised and under-treated. It is therefore crucial that validated nutrition screening and assessment tools are used for early identification of malnutrition. Although many nutrition screening and assessment tools are available, there is no universally accepted method for defining malnutrition risk and nutritional status. Most existing tools have been validated amongst Caucasians using various approaches, but they are rarely reported in the Asian elderly and none has been validated in Singapore. Due to the multiethnicity, cultural, and language differences in Singapore older adults, the results from non-Asian validation studies may not be applicable. Therefore it is important to identify validated population and setting specific nutrition screening and assessment methods to accurately detect and diagnose malnutrition in Singapore. The aims of this study are therefore to: i) characterise hospitalised elderly in a Singapore acute hospital; ii) describe the extent and impact of admission malnutrition; iii) identify and evaluate suitable methods for nutritional screening and assessment; and iv) examine changes in nutritional status during admission and their impact on clinical outcomes. A total of 281 participants, with a mean (+SD) age of 81.3 (+7.6) years, were recruited from three geriatric wards in Tan Tock Seng Hospital over a period of eight months. They were predominantly Chinese (83%) and community-dwellers (97%). They were screened within 72 hours of admission by a single dietetic technician using four nutrition screening tools [Tan Tock Seng Hospital Nutrition Screening Tool (TTSH NST), Nutritional Risk Screening 2002 (NRS 2002), Mini Nutritional Assessment-Short Form (MNA-SF), and Short Nutritional Assessment Questionnaire (SNAQ©)] that were administered in no particular order. The total scores were not computed during the screening process so that the dietetic technician was blinded to the results of all the tools. Nutritional status was assessed by a single dietitian, who was blinded to the screening results, using four malnutrition assessment methods [Subjective Global Assessment (SGA), Mini Nutritional Assessment (MNA), body mass index (BMI), and corrected arm muscle area (CAMA)]. The SGA rating was completed prior to computation of the total MNA score to minimise bias. Participants were reassessed for weight, arm anthropometry (mid-arm circumference, triceps skinfold thickness), and SGA rating at discharge from the ward. The nutritional assessment tools and indices were validated against clinical outcomes (length of stay (LOS) >11days, discharge to higher level care, 3-month readmission, 6-month mortality, and 6-month Modified Barthel Index) using multivariate logistic regression. The covariates included age, gender, race, dementia (defined using DSM IV criteria), depression (defined using a single question “Do you often feel sad or depressed?”), severity of illness (defined using a modified version of the Severity of Illness Index), comorbidities (defined using Charlson Comorbidity Index, number of prescribed drugs and admission functional status (measured using Modified Barthel Index; MBI). The nutrition screening tools were validated against the SGA, which was found to be the most appropriate nutritional assessment tool from this study (refer section 5.6) Prevalence of malnutrition on admission was 35% (defined by SGA), and it was significantly associated with characteristics such as swallowing impairment (malnourished vs well-nourished: 20% vs 5%), poor appetite (77% vs 24%), dementia (44% vs 28%), depression (34% vs 22%), and poor functional status (MBI 48.3+29.8 vs 65.1+25.4). The SGA had the highest completion rate (100%) and was predictive of the highest number of clinical outcomes: LOS >11days (OR 2.11, 95% CI [1.17- 3.83]), 3-month readmission (OR 1.90, 95% CI [1.05-3.42]) and 6-month mortality (OR 3.04, 95% CI [1.28-7.18]), independent of a comprehensive range of covariates including functional status, disease severity and cognitive function. SGA is therefore the most appropriate nutritional assessment tool for defining malnutrition. The TTSH NST was identified as the most suitable nutritional screening tool with the best diagnostic performance against the SGA (AUC 0.865, sensitivity 84%, specificity 79%). Overall, 44% of participants experienced weight loss during hospitalisation, and 27% had weight loss >1% per week over median LOS 9 days (range 2-50). Wellnourished (45%) and malnourished (43%) participants were equally prone to experiencing decline in nutritional status (defined by weight loss >1% per week). Those with reduced nutritional status were more likely to be discharged to higher level care (adjusted OR 2.46, 95% CI [1.27-4.70]). This study is the first to characterise malnourished hospitalised older adults in Singapore. It is also one of the very few studies to (a) evaluate the association of admission malnutrition with clinical outcomes in a multivariate model; (b) determine the change in their nutritional status during admission; and (c) evaluate the validity of nutritional screening and assessment tools amongst hospitalised older adults in an Asian population. Results clearly highlight that admission malnutrition and deterioration in nutritional status are prevalent and are associated with adverse clinical outcomes in hospitalised older adults. With older adults being vulnerable to risks and consequences of malnutrition, it is important that they are systematically screened so timely and appropriate intervention can be provided. The findings highlighted in this thesis provide an evidence base for, and confirm the validity of the current nutrition screening and assessment tools used among hospitalised older adults in Singapore. As the older adults may have developed malnutrition prior to hospital admission, or experienced clinically significant weight loss of >1% per week of hospitalisation, screening of the elderly should be initiated in the community and continuous nutritional monitoring should extend beyond hospitalisation.

Body composition and its relationship to metabolic risk factors in Asian children

Obesity is a major public health problem in both developed and developing countries. The body mass index (BMI) is the most common index used to define obesity. The universal application of the same BMI classification across different ethnic groups is being challenged due to the inability of the index to differentiate fat mass (FM) and fat�]free mass (FFM) and the recognized ethnic differences in body composition. A better understanding of the body composition of Asian children from different backgrounds would help to better understand the obesity�]related health risks of people in this region. Moreover, the limitations of the BMI underscore the necessity to use where possible, more accurate measures of body fat assessment in research and clinical settings in addition to BMI, particularly in relation to the monitoring of prevention and treatment efforts. The aim of the first study was to determine the ethnic difference in the relationship between BMI and percent body fat (%BF) in pre�]pubertal Asian children from China, Lebanon, Malaysia, the Philippines, and Thailand. A total of 1039 children aged 8�]10 y were recruited using a non�]random purposive sampling approach aiming to encompass a wide BMI range from the five countries. Percent body fat (%BF) was determined using the deuterium dilution technique to quantify total body water (TBW) and subsequently derive proportions of FM and FFM. The study highlighted the sex and ethnic differences between BMI and %BF in Asian children from different countries. Girls had approximately 4.0% higher %BF compared with boys at a given BMI. Filipino boys tended to have a lower %BF than their Chinese, Lebanese, Malay and Thai counterparts at the same age and BMI level (corrected mean %BF was 25.7�}0.8%, 27.4�}0.4%, 27.1�}0.6%, 27.7�}0.5%, 28.1�}0.5% for Filipino, Chinese, Lebanese, Malay and Thai boys, respectively), although they differed significantly from Thai and Malay boys. Thai girls had approximately 2.0% higher %BF values than Chinese, Lebanese, Filipino and Malay counterparts (however no significant difference was seen among the four ethnic groups) at a given BMI (corrected mean %BF was 31.1�}0.5%, 28.6�}0.4%, 29.2�}0.6%, 29.5�}0.6%, 29.5�}0.5% for Thai, Chinese, Lebanese, Malay and Filipino girls, respectively). However, the ethnic difference in BMI�]%BF relationship varied by BMI. Compared with Caucasians, Asian children had a BMI 3�]6 units lower for a given %BF. More than one third of obese Asian children in the study were not identified using the WHO classification and more than half were not identified using the International Obesity Task Force (IOTF) classification. However, use of the Chinese classification increased the sensitivity by 19.7%, 18.1%, 2.3%, 2.3%, and 11.3% for Chinese, Lebanese, Malay, Filipino and Thai girls, respectively. A further aim of the first study was to determine the ethnic difference in body fat distribution in pre�]pubertal Asian children from China, Lebanon, Malaysia, and Thailand. The skin fold thicknesses, height, weight, waist circumference (WC) and total adiposity (as determined by deuterium dilution technique) of 922 children from the four countries was assessed. Chinese boys and girls had a similar trunk�]to�]extremity skin fold thickness ratio to Thai counterparts and both groups had higher ratios than the Malays and Lebanese at a given total FM. At a given BMI, both Chinese and Thai boys and girls had a higher WC than Malays and Lebanese (corrected mean WC was 68.1�}0.2 cm, 67.8�}0.3 cm, 65.8�}0.4 cm, 64.1�}0.3 cm for Chinese, Thai, Lebanese and Malay boys, respectively; 64.2�}0.2 cm, 65.0�}0.3 cm, 62.9�}0.4 cm, 60.6�}0.3 cm for Chinese, Thai, Lebanese and Malay girls, respectively). Chinese boys and girls had lower trunk fat adjusted subscapular/suprailiac skinfold ratio compared with Lebanese and Malay counterparts. The second study aimed to develop and cross�]validate bioelectrical impedance analysis (BIA) prediction equations of TBW and FFM for Asian pre�]pubertal children from China, Lebanon, Malaysia, the Philippines, and Thailand. Data on height, weight, age, gender, resistance and reactance measured by BIA were collected from 948 Asian children (492 boys and 456 girls) aged 8�]10 y from the five countries. The deuterium dilution technique was used as the criterion method for the estimation of TBW and FFM. The BIA equations were developed from the validation group (630 children randomly selected from the total sample) using stepwise multiple regression analysis and cross�]validated in a separate group (318 children) using the Bland�]Altman approach. Age, gender and ethnicity influenced the relationship between the resistance index (RI = height2/resistance), TBW and FFM. The BIA prediction equation for the estimation of TBW was: TBW (kg) = 0.231�~Height2 (cm)/resistance (ƒ¶) + 0.066�~Height (cm) + 0.188�~Weight (kg) + 0.128�~Age (yr) + 0.500�~Sex (male=1, female=0) . 0.316�~Ethnicity (Thai ethnicity=1, others=0) �] 4.574, and for the estimation of FFM: FFM (kg) = 0.299�~Height2 (cm)/resistance (ƒ¶) + 0.086�~Height (cm) + 0.245�~Weight (kg) + 0.260�~Age (yr) + 0.901�~Sex (male=1, female=0) �] 0.415�~Ethnicity (Thai ethnicity=1, others=0) �] 6.952. The R2 was 88.0% (root mean square error, RSME = 1.3 kg), 88.3% (RSME = 1.7 kg) for TBW and FFM equation, respectively. No significant difference between measured and predicted TBW and between measured and predicted FFM for the whole cross�]validation sample was found (bias = �]0.1�}1.4 kg, pure error = 1.4�}2.0 kg for TBW and bias = �]0.2�}1.9 kg, pure error = 1.8�}2.6 kg for FFM). However, the prediction equation for estimation of TBW/FFM tended to overestimate TBW/FFM at lower levels while underestimate at higher levels of TBW/FFM. Accuracy of the general equation for TBW and FFM compared favorably with both BMI�]specific and ethnic�]specific equations. There were significant differences between predicted TBW and FFM from external BIA equations derived from Caucasian populations and measured values in Asian children. There were three specific aims of the third study. The first was to explore the relationship between obesity and metabolic syndrome and abnormalities in Chinese children. A total of 608 boys and 800 girls aged 6�]12 y were recruited from four cities in China. Three definitions of pediatric metabolic syndrome and abnormalities were used, including the International Diabetes Federation (IDF) and National Cholesterol Education Program (NCEP) definition for adults modified by Cook et al. and de Ferranti et al. The prevalence of metabolic syndrome varied with different definitions, was highest using the de Ferranti definition (5.4%, 24.6% and 42.0%, respectively for normal�]weight, overweight and obese children), followed by the Cook definition (1.5%, 8.1%, and 25.1%, respectively), and the IDF definition (0.5%, 1.8% and 8.3%, respectively). Overweight and obese children had a higher risk of developing the metabolic syndrome compared to normal�]weight children (odds ratio varied with different definitions from 3.958 to 6.866 for overweight children, and 12.640�]26.007 for obese children). Overweight and obesity also increased the risk of developing metabolic abnormalities. Central obesity and high triglycerides (TG) were the most common while hyperglycemia was the least frequent in Chinese children regardless of different definitions. The second purpose was to determine the best obesity index for the prediction of cardiovascular (CV) risk factor clustering across a 2�]y follow�]up among BMI, %BF, WC and waist�]to�]height ratio (WHtR) in Chinese children. Height, weight, WC, %BF as determined by BIA, blood pressure, TG, high�]density lipoprotein cholesterol (HDL�]C), and fasting glucose were collected at baseline and 2 years later in 292 boys and 277 girls aged 8�]10 y. The results showed the percentage of children who remained overweight/obese defined on the basis of BMI, WC, WHtR and %BF was 89.7%, 93.5%, 84.5%, and 80.4%, respectively after 2 years. Obesity indices at baseline significantly correlated with TG, HDL�]C, and blood pressure at both baseline and 2 years later with a similar strength of correlations. BMI at baseline explained the greatest variance of later blood pressure. WC at baseline explained the greatest variance of later HDL�]C and glucose, while WHtR at baseline was the main predictor of later TG. Receiver�]operating characteristic (ROC) analysis explored the ability of the four indices to identify the later presence of CV risk. The overweight/obese children defined on the basis of BMI, WC, WHtR or %BF were more likely to develop CV risk 2 years later with relative risk (RR) scores of 3.670, 3.762, 2.767, and 2.804, respectively. The final purpose of the third study was to develop age�] and gender�]specific percentiles of WC and WHtR and cut�]off points of WC and WHtR for the prediction of CV risk in Chinese children. Smoothed percentile curves of WC and WHtR were produced in 2830 boys and 2699 girls aged 6�]12 y randomly selected from southern and northern China using the LMS method. The optimal age�] and gender�]specific thresholds of WC and WHtR for the prediction of cardiovascular risk factors clustering were derived in a sub�]sample (n=1845) by ROC analysis. Age�] and gender�]specific WC and WHtR percentiles were constructed. The WC thresholds were at the 90th and 84th percentiles for Chinese boys and girls, respectively, with sensitivity and specificity ranging from 67.2% to 83.3%. The WHtR thresholds were at the 91st and 94th percentiles for Chinese boys and girls, respectively, with sensitivity and specificity ranging from 78.6% to 88.9%. The cut�]offs of both WC and WHtR were age�] and gender�]dependent. In conclusion, the current thesis quantifies the ethnic differences in the BMI�]%BF relationship and body fat distribution between Asian children from different origins and confirms the necessity to consider ethnic differences in body composition when developing BMI and other obesity index criteria for obesity in Asian children. Moreover, ethnicity is also important in BIA prediction equations. In addition, WC and WHtR percentiles and thresholds for the prediction of CV risk in Chinese children differ from other populations. Although there was no advantage of WC or WHtR over BMI or %BF in the prediction of CV risk, obese children had a higher risk of developing the metabolic syndrome and abnormalities than normal�]weight children regardless of the obesity index used.

New percentage body fat prediction equations for Japanese females

Anthropometry is a simple and cost-efficient method for the assessment of body composition. However prediction equations to estimate body composition using anthropometry should be ‘population-specific’. Most popular body composition prediction equations for Japanese females were proposed more than 40 years ago and there is some concern regarding their usefulness in Japanese females living today. The aim of this study was to compare percentage body fat (%BF) estimated from anthropometry and dual energy x-ray absorptiometry (DXA) to examine the applicability of commonly used prediction equations in young Japanese females. Body composition of 139 Japanese females aged between 18 and 27 years of age (BMI range: 15.1–29.1 kg/m2) was measured using whole-body DXA (Lunar DPX-LIQ) scans. From anthropometric measurements %BF was estimated using four equations developed from Japanese females. The results showed that the traditionally employed prediction equations for anthropometry significantly (p<0.01) underestimate %BF of young Japanese females and therefore are not valid for the precise estimation of body composition. New %BF prediction equations were proposed from the DXA and anthropometry results. Application of the proposed equations may assist in more accurate assessment of body fatness in Japanese females living today.

How does the size and shape of local populations in China compare to general anthropometric surveys currently used for product design?

Anthropometry has long been used for a range of ergonomic applications & product design. Although products are often designed for specific cohorts, anthropometric data are typically sourced from large scale surveys representative of the general population. Additionally, few data are available for emerging markets like China and India. This study measured 80 Chinese males that were representative of a specific cohort targeted for the design of a new product. Thirteen anthropometric measurements were recorded and compared to two large databases that represented a general population, a Chinese database and a Western database. Substantial differences were identified between the Chinese males measured in this study and both databases. The subjects were substantially taller, heavier and broader than subjects in the older Chinese database. However, they were still substantially smaller, lighter and thinner than Western males. Data from current Western anthropometric surveys are unlikely to accurately represent the target population for product designers and manufacturers in emerging markets like China.

Determinants of driver vs. second row occupant posture modelling

Digital human modeling (DHM), as a convenient and cost-effective tool, is increasingly incorporated into product and workplace design. In product design, it is predominantly used for the development of driver-vehicle systems. Most digital human modeling software tools, such as JACK, RAMSIS and DELMIA HUMANBUILDER provide functions to predict posture and positions for drivers with selected anthropometry according to SAE (Society of Automotive Engineers) Recommended Practices and other ergonomics guidelines. However, few studies have presented 2nd row passenger postural information, and digital human modeling of these passenger postures cannot be performed directly using the existing driver posture prediction functions. In this paper, the significant studies related to occupant posture and modeling were reviewed and a framework of determinants of driver vs. 2nd row occupant posture modeling was extracted. The determinants which are regarded as input factors for posture modeling include target population anthropometry, vehicle package geometry and seat design variables as well as task definitions. The differences between determinants of driver and 2nd row occupant posture models are significant, as driver posture modeling is primarily based on the position of the foot on the accelerator pedal (accelerator actuation point AAP, accelerator heel point AHP) and the hands on the steering wheel (steering wheel centre point A-Point). The objectives of this paper are aimed to investigate those differences between driver and passenger posture, and to supplement the existing parametric model for occupant posture prediction. With the guide of the framework, the associated input parameters of occupant digital human models of both driver and second row occupant will be identified. Beyond the existing occupant posture models, for example a driver posture model could be modified to predict second row occupant posture, by adjusting the associated input parameters introduced in this paper. This study combines results from a literature review and the theoretical modeling stage of a second row passenger posture prediction model project.

Digital human modelling for vehicle design and manufacturing

Digital human modelling (DHM) has today matured from research into industrial application. In the automotive domain, DHM has become a commonly used tool in virtual prototyping and human-centred product design. While this generation of DHM supports the ergonomic evaluation of new vehicle design during early design stages of the product, by modelling anthropometry, posture, motion or predicting discomfort, the future of DHM will be dominated by CAE methods, realistic 3D design, and musculoskeletal and soft tissue modelling down to the micro-scale of molecular activity within single muscle fibres. As a driving force for DHM development, the automotive industry has traditionally used human models in the manufacturing sector (production ergonomics, e.g. assembly) and the engineering sector (product ergonomics, e.g. safety, packaging). In product ergonomics applications, DHM share many common characteristics, creating a unique subset of DHM. These models are optimised for a seated posture, interface to a vehicle seat through standardised methods and provide linkages to vehicle controls. As a tool, they need to interface with other analytic instruments and integrate into complex CAD/CAE environments. Important aspects of current DHM research are functional analysis, model integration and task simulation. Digital (virtual, analytic) prototypes or digital mock-ups (DMU) provide expanded support for testing and verification and consider task-dependent performance and motion. Beyond rigid body mechanics, soft tissue modelling is evolving to become standard in future DHM. When addressing advanced issues beyond the physical domain, for example anthropometry and biomechanics, modelling of human behaviours and skills is also integrated into DHM. Latest developments include a more comprehensive approach through implementing perceptual, cognitive and performance models, representing human behaviour on a non-physiologic level. Through integration of algorithms from the artificial intelligence domain, a vision of the virtual human is emerging.

The contribution of seat components to seat hardness and the interface between human occupant and a driver seat

Effective digital human model (DHM) simulation of automotive driver packaging ergonomics, safety and comfort depends on accurate modelling of occupant posture, which is strongly related to the mechanical interaction between human body soft tissue and flexible seat components. This paper comprises: a study investigating the component mechanical behaviour of a spring-suspended, production level seat when indented by SAE J826 type, human thigh-buttock representing hard shell; a model of seated human buttock shape for improved indenter design using a multivariate representation of Australian population thigh-buttock anthropometry; and a finite-element study simulating the deflection of human buttock and thigh soft tissue when seated, based on seated MRI. The results of the three studies provide a description of the mechanical properties of the driver-seat interface, and allow validation of future dynamic simulations, involving multi-body and finite-element (FE) DHM in virtual ergonomic studies.

Footprint-based estimates of arch structure are confounded by body composition in adults

Previous research employing indirect measures of arch structure, such as those derived from footprints, have indicated that obesity results in a “flatter” foot type. In the absence of radiographic measures, however, definitive conclusions regarding the osseous alignment of the foot cannot be made. We determined the effect of body mass index (BMI) on radiographic and footprint‐based measures of arch structure. The research was a cross‐sectional study in which radiographic and footprint‐based measures of foot structure were made in 30 subjects (10 males, 20 female) in addition to standard anthropometric measures of height, weight, and BMI. Multiple (univariate) regression analysis demonstrated that both BMI ( β  = 0.39, t 26  = 2.12, p  = 0.04) and radiographic arch alignment ( β  = 0.51, t 26  = 3.32, p  < 0.01) were significant predictors of footprint‐based measures of arch height after controlling for all variables in the model ( R 2  = 0.59, F 3,26  = 12.3, p  < 0.01). In contrast, radiographic arch alignment was not significantly associated with BMI ( β  = −0.03, t 26  = −0.13, p  = 0.89) when Arch Index and age were held constant ( R 2  = 0.52, F 3,26  = 9.3, p  < 0.01). Adult obesity does not influence osseous alignment of the medial longitudinal arch, but selectively distorts footprint‐based measures of arch structure. Footprint‐based measures of arch structure should be interpreted with caution when comparing groups of varying body composition.

Ergonomic DHM systems - limitations and trends – a systematic literature review focused on the ‘future of ergonomics’

Digital Human Models (DHM) have been used for over 25 years. They have evolved from simple drawing templates, which are nowadays still used in architecture, to complex and Computer Aided Engineering (CAE) integrated design and analysis tools for various ergonomic tasks. DHM are most frequently used for applications in product design and production planning, with many successful implementations documented. DHM from other domains, as for example computer user interfaces, artificial intelligence, training and education, or the entertainment industry show that there is also an ongoing development towards a comprehensive understanding and holistic modeling of human behavior. While the development of DHM for the game sector has seen significant progress in recent years, advances of DHM in the area of ergonomics have been comparatively modest. As a consequence, we need to question if current DHM systems are fit for the design of future mobile work systems. So far it appears that DHM in Ergonomics are rather limited to some traditional applications. According to Dul et al. (2012), future characteristics of Human Factors and Ergonomics (HFE) can be assigned to six main trends: (1) global change of work systems, (2) cultural diversity, (3) ageing, (4) information and communication technology (ICT), (5) enhanced competiveness and the need for innovation, and; (6) sustainability and corporate social responsibility. Based on a literature review, we systematically investigate the capabilities of current ergonomic DHM systems versus the ‘Future of Ergonomics’ requirements. It is found that DHMs already provide broad functionality in support of trends (1) and (2), and more limited options in regards to trend (3). Today’s DHM provide access to a broad range of national and international databases for correct differentiation and characterization of anthropometry for global populations. Some DHM explicitly address social and cultural modeling of groups of people. In comparison, the trends of growing importance of ICT (4), the need for innovation (5) and sustainability (6) are addressed primarily from a hardware-oriented and engineering perspective and not reflected in DHM. This reflects a persistent separation between hardware design (engineering) and software design (information technology) in the view of DHM – a disconnection which needs to be urgently overcome in the era of software defined user interfaces and mobile devices. The design of a mobile ICT-device is discussed to exemplify the need for a comprehensive future DHM solution. Designing such mobile devices requires an approach that includes organizational aspects as well as technical and cognitive ergonomics. Multiple interrelationships between the different aspects result in a challenging setting for future DHM. In conclusion, the ‘Future of Ergonomics’ pose particular challenges for DHM in regards to the design of mobile work systems, and moreover mobile information access.

Development and validation of anthropometric prediction equations for estimation of lean body mass and appendicular lean soft tissue in Indian men and women

Lean body mass (LBM) and muscle mass remains difficult to quantify in large epidemiological studies due to non-availability of inexpensive methods. We therefore developed anthropometric prediction equations to estimate the LBM and appendicular lean soft tissue (ALST) using dual energy X-ray absorptiometry (DXA) as a reference method. Healthy volunteers (n= 2220; 36% females; age 18-79 y) representing a wide range of body mass index (14-44 kg/m2) participated in this study. Their LBM including ALST was assessed by DXA along with anthropometric measurements. The sample was divided into prediction (60%) and validation (40%) sets. In the prediction set, a number of prediction models were constructed using DXA measured LBM and ALST estimates as dependent variables and a combination of anthropometric indices as independent variables. These equations were cross-validated in the validation set. Simple equations using age, height and weight explained > 90% variation in the LBM and ALST in both men and women. Additional variables (hip and limb circumferences and sum of SFTs) increased the explained variation by 5-8% in the fully adjusted models predicting LBM and ALST. More complex equations using all the above anthropometric variables could predict the DXA measured LBM and ALST accurately as indicated by low standard error of the estimate (LBM: 1.47 kg and 1.63 kg for men and women, respectively) as well as good agreement by Bland Altman analyses. These equations could be a valuable tool in large epidemiological studies assessing these body compartments in Indians and other population groups with similar body composition.