Body segment inertial parameters and low back load in individuals with central adiposity

There is a paucity of information regarding the impact of central adiposity on the inertial characteristics of body segments. Deriving low back loads during lifting requires accurate estimate of inertial parameters. The purpose was to determine the body segment inertial parameters of people with central adiposity using a photogrammetric technique, and then to evaluate the impact on lumbar spine loading. Five participants with central adiposity (waist:hip ratio>0.9, waist circumference>102 cm) were compared to a normal BMI group. A 3D wireframe model of the surface topography was constructed, partitioned into 8 body segments and then body segment inertial parameters were calculated using volumetric integration assuming uniform segment densities for the segments. Central adiposity dependent increases in body segment parameters ranged from 12 to 400%, varying across segments (greatest for trunk) and parameters. The increase in mass distribution to the trunk was accompanied by an anterior and inferior shift of the centre of mass. A proximal shift in centre of mass was detected for the extremities, along with a reduction in mass distribution to the lower extremity. L5/S1 torques (392 vs 263 Nm) and compressive forces (5918 vs 3986 N) were substantially elevated in comparison to the normal BMI group, as well as in comparison to torques and forces predicted using published BSIP equations. Central adiposity resulted in substantial but non-uniform increases in inertial parameters resulting in task specific increases in torque and compressive loads arising from different inertial and physical components.     

Body segment inertial parameter estimation for the general population of older adults

The practical determination of accurate body segment inertial parameters for the general older adult population remains a problem, especially in estimating these parameters for women and accounting for variations in body type. A method is presented for determining the mass and center of mass location of the body segments of individuals within the general population of older adults. Effects of sex and body type on older adult mass distribution are accounted for using 32 easily obtainable body measurements. The method is based on existing results from different data sources and employs a combination of validated estimation approaches, including: body mass and segment length proportions, linear and nonlinear regression equations, and a mathematical model of the trunk. The method was applied to a validation sample of healthy, community-dwelling older adults (29 men, 50 women). Predicted body mass was 96.7+/-4.8% and 95.7+/-3.7% of measured body mass in the men and women, respectively. The estimates of body segment mass and trunk center of mass location for the sample population approximate those reported in the literature, supporting the validity of the described method. By producing practical, subject-specific estimates of body segment inertial parameters, the method should allow more accurate biomechanical analyses of the older adult population.     

Predicting in vivo soft tissue masses of the lower extremity using segment anthropometric measures and DXA

The purpose of this study was to derive and validate regression equations for the prediction of fat mass (FM), lean mass (LM), wobbling mass (WM), and bone mineral content (BMC) of the thigh, leg, and leg + foot segments of living people from easily measured segmental anthropometric measures. The segment masses of 68 university-age participants (26 M, 42 F) were obtained from full-body dual photon x-ray absorptiometry (DXA) scans, and were used as the criterion values against which predicted masses were compared. Comprehensive anthropometric measures (6 lengths, 6 circumferences, 8 breadths, 4 skinfolds) were taken bilaterally for the thigh and leg for each person. Stepwise multiple linear regression was used to derive a prediction equation for each mass type and segment. Prediction equations exhibited high adjusted R2 values in general (0.673 to 0.925), with higher correlations evident for the LM and WM equations than for FM and BMC. Predicted (equations) and measured (DXA) segment LM and WM were also found to be highly correlated (R2 = 0.85 to 0.96), and FM and BMC to a lesser extent (R2 = 0.49 to 0.78). Relative errors between predicted and measured masses ranged between 0.7% and -11.3% for all those in the validation sample (n = 16). These results on university-age men and women are encouraging and suggest that in vivo estimates of the soft tissue masses of the lower extremity can be made fairly accurately from simple segmental anthropometric measures.     

Using mass distribution information to model the human thigh for body segment parameter estimation

Accurate estimations of body segment inertial parameters (BSPs) are required to calculate the kinetics of motion. The purpose of this study was to develop a geometric model of the human thigh segment based on mass distribution properties determined from dual energy x ray absorptiometry (DEXA). One hundred subjects from four populations underwent a DEXA scan and anthropometric measurements were taken. The mass distribution properties of the thigh segment were determined for 20 subjects, a geometric model was developed, and the model was applied to the remaining 80 subjects. The model was validated by comparing to benchmark DEXA measurements. Four other popular models in the literature were also evaluated in the same manner No one set of predictors performed best for a particular group or BSP, however modeling the mass distribution properties of the segment allows the assumption of constant density while still accurately representing the inertial properties of the segment and provides promise for future development of BSP models.     

Prehistoric mongoloid dispersals. Edited by Takeru Akazawa and Emöke J. E. Szathmáry. New York: Oxford University Press. 1996. 387 pp. ISBN 0-19-852318-1 $150.00 (cloth)

Studies of the dynamics of locomotor performances depend on knowledge of the distribution of body mass within and between limb segments. However, these data are difficult to derive. Segment mass properties have generally been estimated by modelling limbs as truncated cones, but this approach fails to take into account that some segments are of elliptical, not circular, cross section; and further, the profiles of real segments are generally curved. Thus, they are more appropriately modelled as solids of revolution, described by the rotation in space of convex or concave curves, and the possibility of an elliptical cross section needs to be taken into account. In this project we have set out to develop a general geometric model which can take these factors into account, and permit segment inertial properties to be derived from cadavers by segmentation, and from living individuals using linear external measurements. We present a model which may be described by up to four parameters, depending o the profile and serial cross section (circular or ellipsoidal) of the individual segments. The parameters are obtained from cadavers using a simplified complex-pendulum technique, and from intact specimens by calculation from measurements of segment diameters and lengths. From the parameters, the center of mass, moments of inertia, and radii of gyration may be derived, using simultaneous equations. Inertial properties of the body segments of four Pan troglodytes and a single Pongo were determined, and contrasted to comparable findings for humans. Using our approach, the mass distribution characteristics of any individual or species may be represented by a rigid-link segment model or “android.” If this is made to move according to motion functions derived from a real performance of the individual represented, we show that recordings of resulting ground reaction forces may be quite closely simulated by predictive dynamic modelling. © 1996 Wiley-Liss, Inc.     

Analysis of body segment parameter differences between four human populations and the estimation errors of four popular mathematical models

Calculating the kinetics of motion using inverse or forward dynamics methods requires the use of accurate body segment inertial parameters. The methods available for calculating these body segment parameters (BSPs) have several limitations and a main concern is the applicability of predictive equations to several different populations. This study examined the differences in BSPs between 4 human populations using dual energy x-ray absorptiometry (DEXA), developed linear regression equations to predict mass, center of mass location (CM) and radius of gyration (K) in the frontal plane on 5 body segments and examined the errors produced by using several BSP sources in the literature. Significant population differences were seen in all segments for all populations and all BSPs except hand mass, indicating that population specific BSP predictors are needed. The linear regression equations developed performed best overall when compared to the other sources, yet no one set of predictors performed best for all segments, populations or BSPs. Large errors were seen with all models which were attributed to large individual differences within groups. Equations which account for these differences, including measurements of limb circumferences and breadths may provide better estimations. Geometric models use these parameters, however the models examined in this study did not perform well, possibly due to the assumption of constant density or the use of an overly simple shape. Creating solids which account for density changes or which mimic the mass distribution characteristics of the segment may solve this problem. Otherwise, regression equations specific for populations according to age, gender, race, and morphology may be required to provide accurate estimations of BSPs for use in kinetic equations of motion.     

Changes in segmental inertial properties with age

The purpose of this study was to examine how the limb segment inertial parameters vary across the decades from the 1920s to the 1970s. Sixty-six males participated in this study, ranging in age from 20 to 79 years. Pre-screening ensured that all subjects were healthy. The inertial properties of the segments were determined by modeling each segment as series of geometric solids. A multivariate analysis of variance (ANOVA) revealed statistically significant differences between decade age groups for the upper arm, forearm, shank, and thigh (p<0.01). Subsequent ANOVAs revealed statistically significant differences for all the inertial properties for the upper arm, the center of mass location for the forearm, and segment mass for the thigh. Linear regression lines were fit to the data so that each inertial parameter for each segment could be predicted by subject's age, with the slope of this regression line indicating the trend in the data. These trends were statistically significant for all forearm inertial parameters, thigh mass and longitudinal moment of inertia, and forearm center of mass location. The changes for the thigh, upper arm, and forearm were consistent with the changes, which would accompany a change in muscle mass with aging. Resultant joint moments were computed for a set of gait data using inertial properties reflective of the subjects from the age extremes in the study. The resulting differences in the knee and hip moments, young versus old, were all less than 4.5%.     

Changes in body segment inertial parameters of obese individuals with weight loss

Forward dynamic simulation of human movement has the potential to investigate the biomechanical effects of weight loss in obese individuals. However, guidelines for altering body segment inertial parameters (BSIPs) of a biomechanical model to approximate changes that occur with weight loss are currently unavailable. Therefore, the goal of this study was to quantify three-dimensional changes in BSIPs with weight loss. Nineteen Caucasian men of age 43.6+/-7.5 years (mean+/-standard deviation) were evaluated. Body mass and body mass index prior to weight loss were 102.7+/-3.6 kg and 32.6+/-3.2 kg/m2, respectively. Both before and after weight loss, magnetic resonance imaging scans were acquired along the length of the body to discriminate muscle, bone, organ, and adipose tissues. Segment masses, center of mass (COM) positions, and radii of gyration were determined from these scans using published tissue densities and established methods. A number of significant changes in BSIPs occurred with the 13.8+/-2.4% average weight loss. Mass decreased in all segments. COM position moved distally for the thigh and upper arm, superiorly for the trunk, and inferiorly for the whole body. Radius of gyration, in general, decreased in all segments. The changes in BSIPs with weight loss reported here could be used in forward dynamic simulations investigating the biomechanical implications of weight loss.     

Anthropometric and biomechanical characteristics of body segments in persons with spinal cord injury

People with spinal cord injury (SCI) experience bone and muscle loss in their paralyzed limbs that is most rapid and severe in the first 3 years after injury. Restoration of mechanical loading through therapeutic physical activity may potentially slow or reverse post-SCI bone loss, however, therapeutic targets cannot be developed without accurate biomechanical models. Obesity is prevalent among SCI population, and it alters body composition and further affects parameters of these models. Here, clinical whole body dual-energy X-ray absorptiometry data from people with acute (n = 39) and chronic (n = 61) SCI were analyzed to obtain anthropometric parameters including segment masses, center of mass location, and radius of gyration for both obese and non-obese individuals. Chronic SCI was associated with higher normalized trunk mass of 3.2%BW and smaller normalized leg mass of 1.8%BW in males, but no significant changes in segment centers of mass or radius of gyration. People with chronic SCI had 58.6% lean mass in the trunk, compared to 66.6% lean mass in those with acute SCI (p = 0.01), with significant changes in all segments. Obesity was associated with an increase in trunk mass proportion of 3.1%BW, proximal shifts in thigh and upper arm center of mass, and changes to thigh and shank radius of gyration. The data presented here can be used to accurately represent the anthropometrics of SCI population in biomechanical studies, considering obesity and injury duration.     

Body segment mass, radius and radius of gyration proportions of children

The segment inertial parameters of children are fundamental to the analysis and simulation of their movements. Generally it has been recognized that adult parameters cannot be extrapolated and most of the anthropometric data on children are of little or no use for determining inertias. Consequently, there have been few studies of children's kinetics. In response to this problem a longitudinal investigation, the Laurentian Study of Biomechanical Development, was launched and in this paper the effects of growth on selected segmental size and inertial parameters are reported for boys between the ages of 4 and 15 yr. The twelve subjects, representing heterogeneous body types were followed over 3 yr for a total of 36 observations. Elliptical zones 2 cm wide were used to model the body and segment inertias calculated using segment densities from the literature. These inertias were the mass, moment of inertia and mass centroid location for a fourteen segment planar representation of the body. The general accuracy mean error based on body mass was 0.203% which is consistent with reports from similar studies and techniques. Plots of segment mass proportions with respect to age showed a decrease in the head proportion balanced by increases in the thigh, shank, foot and upper arm proportions in particular. The trends for each segment were consistent with the trends for linear measures reported in the anthropometry literature. Radius proportions to the mass centroid and radius of gyration proportions were also plotted and showed smaller but consistent changes with respect to age. Linear regressions were then fitted to the distributions and standard errors calculated. The magnitude and slope of the regressions were for the most part consistent with a reported cross-sectional study of Japanese children. Where data were available, predicted parameters were compared with the reported parameters for a 12 yr old analyzed using a different mathematical model. Comparisons were also made between the predicted parameters at 15 yr and the reported parameters for healthy young adults who had been scanned using a gamma-radiation technique. For most parameters there was either good agreement or differences could be explained logically. The traditionally used parameters from older cadavers were quite inconsistent with the above. The variances of the 36 observations about the regression lines as indicated by the standard errors were small. As an illustration of the effect of these variances, the trunk parameters for a 10 yr old performing a standing jump for distance were decreased by 1 S.E. and this matched by increases for the thigh, shank and head.(ABSTRACT TRUNCATED AT 400 WORDS)     

Adjustments to the segment center of mass proportions of Clauser et al. (1969)

One of the most commonly-referenced studies on body segment masses and centers of mass is by Clauser et al. (AMRL Technical Report 69-70, Wright Patterson Air Force Base, 1969). The Clauser et al. data, however, are difficult to use, because the investigators used certain bony landmarks rather than joint centers as reference points for the center of mass proportions. The purpose of this study was to make adjustments to those proportions so that they could be applied directly to segments having joint centers as endpoints. The segments affected by these adjustments were the trunk, upper arm, forearm, thigh, and calf. These new proportions are markedly different than those originally reported by Clauser et al., especially for the trunk segment. Readers are cautioned against using the original proportions when using joint centers as segment endpoints.     

Mass, center of mass, and moment of inertia estimates for infant limb segments.

To quantify limb dynamics, accurate estimates are needed of anthropometric inertia parameters (mass, center-of-mass location, and moments of inertia). These estimates, however, are not available for human infants; therefore, the movement dynamics of infants have not been studied extensively. Here, regression equations for the masses, center-of-mass locations, and transverse moments of inertia of upper and lower limb segments (upper arm, forearm, and hand; thigh, leg, and foot) of 0.04 to 1.50 yr old infants are provided. A mathematical model of the human body was used to determine the anthropometric inertia parameters for upper limbs in 44 infants and for lower limbs in 70 infants. Stepwise linear regressions were used to fit the distributions of the anthropometric inertia parameters. The regression equations accounted for significant amounts of the variance (64-98%), and the R2-values compared favorably when our equations were cross-validated. Consequently, these regression equations can provide, for infants of similar ages, reasonable estimates of upper and lower limb anthropometric inertia parameters, suitable for equations of motion in the analysis of limb dynamics in human infants.     

A comparison of methods to determine center of mass during pregnancy

Balance changes during pregnancy likely occur because of mass gains and mass distribution changes. However, to date there is no way of tracking balance through center of mass motion because no method is available to identify of the body center of mass throughout pregnancy. We compared methods for determining segment masses and torso center of mass location. The availability of a method for tracking these changes during pregnancy will make determining balance changes through center of mass motion an option for future pregnancy balance research. Thirty pregnant women from eight weeks gestation until birth were recruited for monthly anthropometric measurements, motion capture analysis of body segment locations, and force plate analysis of center of pressure during quiet standing and supine laying. From these measurements, we were able to compare regression, volume measurement, and weighted sum methods to calculate body center of mass throughout pregnancy. We found that mass changes around the trunk were most prevalent as expected, but mass changes throughout the body (especially the thighs) were also seen. Our findings also suggest that a series of anthropometric measurements first suggested by Pavol et al. (2002), in combination with quiet standing on a force plate, can be used to identify the needed components (segment masses and torso center of mass location in three dimensions) to calculate body center of mass changes during pregnancy. The results of this study will make tracking of center of mass motion a possibility for future pregnancy balance research.     

Reliability of upper and lower extremity anthropometric measurements and the effect on tissue mass predictions

Accurate modeling of soft tissue motion effects relative to bone during impact requires knowledge of the mass of soft and rigid tissues in living people. Holmes et al., [2005. Predicting in vivo soft tissue masses of the lower extremity using segment anthropometric measures and DXA. Journal of Applied Biomechanics, 21, 371–382] developed and validated regression equations to predict the individual tissue masses of lower extremity segments of young healthy adults, based on simple anthropometric measurements. However, the reliability of these measurements and the effect on predicted tissue mass estimates from the equations has yet to be determined. In the current study, two measurers were responsible for collecting two sets of unilateral measurements (25 male and 25 female subjects) for the right upper and lower extremities. These included 6 lengths, 6 circumferences, 8 breadths, and 4 skinfold thicknesses. Significant differences were found between measurers and between sexes, but these differences were relatively small in general (75–80% of between-measurer differences were <1 cm). Within-measurer measurement differences were smaller and more consistent than those between measurers in most cases. Good to excellent reliability was demonstrated for all measurement types, with intra-class correlation coefficients of 0.79, 0.86, 0.85 and 0.86 for lengths, circumferences, breadth and skinfolds, respectively. Predicted tissue mass magnitudes were moderately affected by the measurement differences. The maximum mean errors between measurers ranged from 3.2% to 24.2% for bone mineral content and fat mass, for the leg and foot, and the leg segments, respectively.     

Prediction of body volume by a stepwise linear regression technique

Body volume and 35 anthropometric measurements were obtained from 88 active soldiers using standard techniques. These anthropometric measurements were examined for their possible relationships to body volume using stepwise linear regression analysis. Four measurements (Body weight, anterior thigh skinfold thickness, subscapular skinfold thickness and suprailiac skinfold thickness) accounted for 99.7% of the variation in body volume and the introduction of each of these measurements in the equation was significant. The regression equation for predicting body volume from these 4 anthropometric measurements had a multiple correlation coefficient of 0.9987 (P less than 0.001). Body weight alone was correlated with body volume to the extent of 0.9966. An attempt has therefore been made to develop a multiple linear regression equation without incorporation of body weight in the regression analysis. Nine measurements were selected by stepwise linear regression analysis for predicting body volume. These nine measurements accounted for 97.1% of the variation in body volume. These equations have been validated on another small sample of 22 soldiers. The analysis has also revealed that a direct regression of body density from the anthropometric variables gives more accurate results than when estimated body volumes are utilized for calculating body density.     

A sensitivity analysis method for the body segment inertial parameters based on ground reaction and joint moment regressor matrices

This paper presents a method allowing a simple and efficient sensitivity analysis of dynamics parameters of complex whole-body human model. The proposed method is based on the ground reaction and joint moment regressor matrices, developed initially in robotics system identification theory, and involved in the equations of motion of the human body. The regressor matrices are linear relatively to the segment inertial parameters allowing us to use simple sensitivity analysis methods. The sensitivity analysis method was applied over gait dynamics and kinematics data of nine subjects and with a 15 segments 3D model of the locomotor apparatus. According to the proposed sensitivity indices, 76 segments inertial parameters out the 150 of the mechanical model were considered as not influent for gait. The main findings were that the segment masses were influent and that, at the exception of the trunk, moment of inertia were not influent for the computation of the ground reaction forces and moments and the joint moments. The same method also shows numerically that at least 90% of the lower-limb joint moments during the stance phase can be estimated only from a force-plate and kinematics data without knowing any of the segment inertial parameters.     

The simulation of aerial movement--II. A mathematical inertia model of the human body

A mathematical inertia model which permits the determination of personalized segmental inertia parameter values from anthropometric measurements is described. The human body is modelled using 40 geometric solids which are specified by 95 anthropometric measurements. A 'stadium' solid is introduced for modelling the torso segments using perimeter and width measurements. This procedure is more accurate than the use of elliptical discs of given width and depth and permits a smaller number of such solids to be used. Inertia parameter values may be obtained for body models of up to 20 segments. Errors in total body mass estimates from this and other models are discussed with reference to the unknown lung volumes.     

A new geometric-based model to accurately estimate arm and leg inertial estimates

Segment estimates of mass, center of mass and moment of inertia are required input parameters to analyze the forces and moments acting across the joints. The objectives of this study were to propose a new geometric model for limb segments, to evaluate it against criterion values obtained from DXA, and to compare its performance to five other popular models. Twenty five female and 24 male college students participated in the study. For the criterion measures, the participants underwent a whole body DXA scan, and estimates for segment mass, center of mass location, and moment of inertia (frontal plane) were directly computed from the DXA mass units. For the new model, the volume was determined from two standing frontal and sagittal photographs. Each segment was modeled as a stack of slices, the sections of which were ellipses if they are not adjoining another segment and sectioned ellipses if they were adjoining another segment (e.g. upper arm and trunk). Length of axes of the ellipses was obtained from the photographs. In addition, a sex-specific, non-uniform density function was developed for each segment. A series of anthropometric measurements were also taken by directly following the definitions provided of the different body segment models tested, and the same parameters determined for each model. Comparison of models showed that estimates from the new model were consistently closer to the DXA criterion than those from the other models, with an error of less than 5% for mass and moment of inertia and less than about 6% for center of mass location.     

Predictive regression modeling of body segment parameters using individual-based anthropometric measurements

Body segment parameters such as segment mass, center of mass, and radius of gyration are used as inputs in static and dynamic ergonomic and biomechanical models used to predict joint and muscle forces, and to assess risks of musculoskeletal injury. Previous work has predicted body segment parameters (BSPs) in the general population using age and obesity levels as statistical predictors (Merrill et al., 2017). Estimated errors in the prediction of BSPs can be as large as 40%, depending on age, and the prediction method employed (Durkin and Dowling, 2003). Thus, more accurate and representative segment parameter inputs are required for attempting to predict modeling outputs such as joint contact forces, muscle forces, and injury risk in individuals. This study aims to provide statistical models for predicting torso, thigh, shank, upper arm, and forearm segment parameters in working adults using whole body dual energy x-ray absorptiometry (DXA) scan data along with a set of anthropometric measurements. The statistical models were developed on a training data set, and independently validated on a separate test data set. The predicted BSPs in validation data were, on average, within 5% of the actual in vivo DXA-based BSPs, while previously developed predictions (de Leva, 1996) had average errors of up to 60%, indicating that the new models greatly increase the accuracy in predicting segment parameters. These final developed models can be used for calculating representative BSPs in individuals for use in modeling applications dependent on these parameters.     

Body Compartment and Subcutaneous Adipose Tissue Distribution - Risk Factor Patterns in Obese Subjects

The purpose of this study was to investigate whether upper body obesity and/or visceral obesity are related to cardiovascular risk factors among severely obese subjects, phenomena that have previously been reported in more heterogeneous body weight distri -buttons. 2450 severely obese men and women aged 37 to 59 years, with a body mass index of 39 ± 4.5 kg/m² (mean ± SD) were examined cross-sectionally. Eight cardiovascular risk factors were studied in relation. to the following body composition indicators: four trunk and three limb circumferences, along with weight, height and sagittal trunk diameter. From the latter three measurements lean body mass (LBM, i.e., the non-adipose tissue mass) and the masses of subcutaneous and visceral adipose tissue were estimated by using sex-specific prediction equations previously calibrated by computed tomography. Two risk factor patterns could be distinguished: 1. One body compartment- risk factor pattern in which the subcutaneous adipose tissue (AT) mass and, in particular, the visceral AT mass were positively related to most risk factors while the lean body mass was negatively related to some risk factors. 2. One subcutaneous adipose tissue distribution- risk factor pattern in which the neck circumference was positively and the thigh circumference negatively related to several risk factors. It is concluded that lean body mass (LBM), visceral and subcutaneous adipose tissue masses as well as neck and thigh circumferences, used as indices of subcutaneous adipose tissue distribution, are independently related to cardiovascular risk factors in severely obese men and women.