Body Segment Masses Research Articles

Associations between Body Segment Mass and Punch, Front Kick, or Countermovement Jump Performance in Military Cadets.

Despite the recognized influence of body mass on combat techniques, the relationship between body segment mass (BSM) and combat moves remains unexplored. This study aimed to examine the relationship between the striking arm mass (SAM), kicking leg mass (KLM), and body mass (BM) and the dynamic forces of direct punch (DP), palm strike (PS), elbow strike (ES), front kick (FK), and countermovement jump (CMJ) performance. Sixteen male military cadets (22.3 ± 1.8 years, 181.4 ± 7.0 cm, 82.1 ± 8.5 kg) performed combat techniques, with their performance measured by using a force plate and their body segment mass assessed by dual-energy X-ray absorptiometry. Spearman's correlation analysis, the Wilcoxon test, and Cohen's d were applied. The results indicated the relationship between the KLM or BM and the FK impulse (r = 0.64, p = 0.01; r = 0.52, p = 0.04, respectively) and CMJ impact force (r = 0.80, p ≤ 0.01; r = 0.70, p ≤ 0.01, respectively). The FK peak and impact forces were moderately correlated with the CMJ jump height (r = 0.74, p ≤ 0.01; r = 0.77, p ≤ 0.01). Moreover, the FK peak force was significantly higher than that for DP, PS, and ES (p ≤ 0.01, d = 3.32; p ≤ 0.01, d = 1.6; and p = 0.013, d = 1.3, respectively). The highest relationship was found between the KLM and the FK impulse; however, the difference in variability explained by the KLM versus the body mass was only 12%. This suggests that knowledge of the BSM did not provide a significantly better estimate of the dynamic forces of the punches and FKs than the knowledge of the BM.

AddBiomechanics: Automating model scaling, inverse kinematics, and inverse dynamics from human motion data through sequential optimization.

Creating large-scale public datasets of human motion biomechanics could unlock data-driven breakthroughs in our understanding of human motion, neuromuscular diseases, and assistive devices. However, the manual effort currently required to process motion capture data and quantify the kinematics and dynamics of movement is costly and limits the collection and sharing of large-scale biomechanical datasets. We present a method, called AddBiomechanics, to automate and standardize the quantification of human movement dynamics from motion capture data. We use linear methods followed by a non-convex bilevel optimization to scale the body segments of a musculoskeletal model, register the locations of optical markers placed on an experimental subject to the markers on a musculoskeletal model, and compute body segment kinematics given trajectories of experimental markers during a motion. We then apply a linear method followed by another non-convex optimization to find body segment masses and fine tune kinematics to minimize residual forces given corresponding trajectories of ground reaction forces. The optimization approach requires approximately 3-5 minutes to determine a subject's skeleton dimensions and motion kinematics, and less than 30 minutes of computation to also determine dynamically consistent skeleton inertia properties and fine-tuned kinematics and kinetics, compared with about one day of manual work for a human expert. We used AddBiomechanics to automatically reconstruct joint angle and torque trajectories from previously published multi-activity datasets, achieving close correspondence to expert-calculated values, marker root-mean-square errors less than 2 cm, and residual force magnitudes smaller than 2% of peak external force. Finally, we confirmed that AddBiomechanics accurately reproduced joint kinematics and kinetics from synthetic walking data with low marker error and residual loads. We have published the algorithm as an open source cloud service at AddBiomechanics.org, which is available at no cost and asks that users agree to share processed and de-identified data with the community. As of this writing, hundreds of researchers have used the prototype tool to process and share about ten thousand motion files from about one thousand experimental subjects. Reducing the barriers to processing and sharing high-quality human motion biomechanics data will enable more people to use state-of-the-art biomechanical analysis, do so at lower cost, and share larger and more accurate datasets.

Body composition and anthropometrics of young male swimmers in relation to the tethered swimming and kinematics of 100-m front crawl race.

The aim was to analyze the relationship of body mass and predicted muscle mass of body segments on swimming kinematics and tethered swimming indices, and further assess the influence of those indices on 100-m front crawl performance of adolescent male swimmers. In 19 volunteer swimmers (age: 13.5±0.44 years, height: 168.6±7.77 cm, body mass: 56.9±10.57 kg), the predicted muscle mass of body segments was assessed with bioelectrical impedance analysis. The kinematic indices of swimming (stroke rate - SR, stroke length - SL, and stroke index - SI) were calculated from a video recording of a 100-m front crawl race. The strength indices (maximum and average value of force, average impulse per single cycle, force decline) were collected in a 30-second front crawl tethered swimming test. The average tethered swimming force was positively correlated with surface swimming speed (0.505; P≤0.05). Indices of SL, SI were influenced by average impulse per single cycle (0.58, 0.55; P≤0.05), and further the SI was strongly correlated with most specified speed indices of the 100-m race (0.59; P≤0.05). It can be stated that the ability of force development in a single stroke, owing to strong interrelation with SI, is a good predictor in talent identification among young swimmers.

Is subject-specific musculoskeletal modelling worth the extra effort or is generic modelling worth the shortcut?

The majority of musculoskeletal modelling studies investigating healthy populations use generic models linearly scaled to roughly match an individual’s anthropometry. Generic models disregard the considerable variation in musculoskeletal geometry and tissue properties between individuals. This study investigated the physiological implications of personalizing musculoskeletal model geometry (body segment mass, inertia, joint center, and maximum isometric muscle force). Nine healthy athletes performed ten repetitions of 15 meter sprints at 75–95% of their maximum sprinting speed and ten repetitions of unanticipated sidestep cut trials with a 4.5–5.5 m/s approach running speed. Structural magnetic resonance imaging was collected on the lower extremities, from which subject-specific musculoskeletal models were developed. A one-dimensional statistical parametric mapping paired t-test was used to compare generic and subject-specific musculoskeletal models for: lower-limb kinematics, kinetics, torque matching, as well as hamstrings, adductors, and quadriceps muscle activations and fiber dynamics. Percentage change of geometric parameters between generic and subject-specific models were determined. Compared to generic models, subject-specific models showed significantly lower ankle dorsi/plantar flexion angle during sprinting and several significantly different net joint moments during sprint and cut tasks. Additionally, subject-specific models demonstrated better torque matching, more physiologically plausible fiber lengths, higher fiber velocities, lower muscle forces, and lower simulated activations in a subset of investigated muscles and motor tasks. Furthermore, subject-specific models identified between-limb differences that were not identified with generic models. Use of subject-specific modeling, even in healthy populations, may result in more physiologically plausible muscle fiber mechanics. Implementing subject-specific models may be especially beneficial when investigating populations with substantial geometric between-limb differences, or unilateral musculoskeletal pathologies, as these are not captured by a generic model.

Quantifying avian inertial properties using calibrated computed tomography.

ABSTRACTEstimating centre of mass and mass moments of inertia is an important aspect of many studies in biomechanics. Characterising these parameters accurately in three dimensions is challenging with traditional methods requiring dissection or suspension of cadavers. Here, we present a method to quantify the three-dimensional centre of mass and inertia tensor of birds of prey using calibrated computed tomography (CT) scans. The technique was validated using several independent methods, providing body segment mass estimates within approximately 1% of physical dissection measurements and moment of inertia measurements with a 0.993 R2 correlation with conventional trifilar pendulum measurements. Calibrated CT offers a relatively straightforward, non-destructive approach that yields highly detailed mass distribution data that can be used for three-dimensional dynamics modelling in biomechanics. Although demonstrated here with birds, this approach should work equally well with any animal or appendage capable of being CT scanned.

Baseball Pitching Arm Three-Dimensional Inertial Parameter Calculations From Body Composition Imaging and a Novel Overweight Measure for Youth Pitching Arm Kinetics.

Many baseball pitching studies have used inverse dynamics to assess throwing arm kinetics as high and repetitive kinetics are thought to be linked to pitching injuries. However, prior studies have not used participant-specific body segment inertial parameters (BSIPs), which are thought to improve analysis of high-acceleration motions and overweight participants. This study's objectives were to (1) calculate participant-specific BSIPs using dual energy X-ray absorptiometry (DXA) measures, (2) compare inverse dynamic calculations of kinetics determined by DXA-calculated BSIPs (full DXA-driven inverse dynamics) against kinetics using the standard inverse dynamics approach with scaled BSIPs (scaled inverse dynamics), and (3) examine associations between full DXA-driven kinetics and overweight indices: body mass index (BMI) and segment mass index (SMI). Eighteen participants (10-11 years old) threw 10 fastballs that were recorded for motion analysis. DXA scans were used to calculate participant-specific BSIPs (mass, center of mass, radii of gyration) for each pitching arm segment (upper arm, forearm, hand), BMI, and SMI. The hypotheses were addressed with t-tests and linear regression analyses. The major results were that (1) DXA-calculated BSIPs differed from scaled BSIPs for each pitching arm segment; (2) calculations for shoulder, but not elbow, kinetics differed between the full DXA-driven and scaled inverse dynamics analyses; and (3) full DXA-driven inverse dynamics calculations for shoulder kinetics were more often associated with SMI than BMI. Results suggest that using participant-specific BSIPs and pitching arm, SMIs may improve evidence-based injury prevention guidelines for youth pitchers.

Relationship Between Body Segment Mass and Running Performance in Well-Trained Endurance Runners.

This study examined the relationship between body segment mass and running performance in endurance runners. The total (muscle, fat, and bone masses), lean (muscle mass), and fat masses of the leg, arm, and trunk segments in 37 well-trained endurance runners were measured using dual-energy X-ray absorptiometer. The relative segment mass was calculated by normalizing the absolute mass to body mass. There were no significant correlations between absolute total, lean, and fat masses of all 3 segments and personal best 5000-m race time. No significant correlations were also observed between all 3 relative masses of the arm segment and personal best 5000-m race time. In contrast, medium positive correlations were observed between the relative total and lean masses of the leg segment and personal best 5000-m race time (r = .387 and .335, respectively, both P ≤ .031). Furthermore, large negative correlations were observed between the relative total and lean masses of the trunk segment and personal best 5000-m race time (r = -.500 and -.548, respectively, both P ≤ .002). These findings suggest that a mass distribution with smaller leg mass and greater trunk mass may be advantageous for achieving better running performance in endurance runners.

Finite element modeling and parameter identification of the seated human body exposed to vertical vibration

Developing a biomechanical model which connected with the actual anatomy of the human body is helpful to understand the human response to vibration. A finite element model of the seated human body with 175 cm in stature and 68.6 kg in weight, which consists of seven segments, six joints and soft tissue, was established to reflect apparent mass based on the Hybrid III dummy model. By comparing the body segment mass percentages with previous data, the rationality of mass distribution in this model was verified. The biomechanical parameters play a crucial role in biodynamic modeling, while the joint and soft tissue parameters are difficult to choose due to the wide range of anthropometric parameters. In this study, the root-mean-square error between the calculated and the measured apparent mass was taken as objective function, and the effect of fifteen human parameters on the objective function was analyzed through sensitivity analysis. Then seven parameters with a considerable influence on the objective function were selected as design variables, and four approximate models were established for parameter optimization. Soft tissues and joint parameters of the model were determined by parameter identification, and the finite element model that can reflect vertical in-line and fore-and-aft cross-axis apparent mass of the human body without backrest was developed. The seated human model presented in this paper can also reflect the transmissibility from seat to the first thoracic spine and the main modes of the human body below 10 Hz, which is conducive to express the human response to vibration.

Explaining Discrepancies Between Total and Segmental DXA and BIA Body Composition Estimates Using Bayesian Regression

Introduction/Background: Few investigations have sought to explain discrepancies between dual-energy X-ray absorptiometry (DXA) and bioelectrical impedance analysis (BIA) body composition estimates. The purpose of this analysis was to explore physiological and anthropometric predictors of discrepancies between DXA and BIA total and segmental body composition estimates. Methodology: Assessments via DXA (GE Lunar Prodigy) and single-frequency BIA (RJL Systems Quantum V) were performed in 179 adults (103 F, 76 M, age: 33.6 ± 15.3 yr; BMI: 24.9 ± 4.3 kg/m2). Potential predictor variables for differences between DXA and BIA total and segmental fat mass (FM) and lean soft tissue (LST) estimates were obtained from demographics and laboratory techniques, including DXA, BIA, bioimpedance spectroscopy, air displacement plethysmography, and 3-dimensional optical scanning. To determine meaningful predictors, Bayesian robust regression models were fit using a t-distribution and regularized hierarchical shrinkage “horseshoe” prior. Standardized model coefficients (β) were generated, and leave-one-out cross validation was used to assess model predictive performance. Results: LST hydration (i.e., total body water:LST) was a predictor of discrepancies in all FM and LST variables (|β|: 0.20–0.82). Additionally, extracellular fluid percentage was a predictor for nearly all outcomes (|β|: 0.19–0.40). Height influenced the agreement between whole-body estimates (|β|: 0.74–0.77), while the mass, length, and composition of body segments were predictors for segmental LST estimates (|β|: 0.23–3.04). Predictors of segmental FM errors were less consistent. Select sex-, race-, or age-based differences between methods were observed. The accuracy of whole-body models was superior to segmental models (leave-one-out cross-validation-adjusted R2 of 0.83–0.85 for FMTOTAL and LSTTOTAL vs. 0.20–0.76 for segmental estimates). For segmental models, predictive performance decreased in the order of: appendicular lean soft tissue, LSTLEGS, LSTTRUNK and FMLEGS, FMARMS, FMTRUNK, and LSTARMS. Conclusions: These findings indicate the importance of LST hydration, extracellular fluid content, and height for explaining discrepancies between DXA and BIA body composition estimates. These general findings and quantitative interpretation based on the presented data allow for a better understanding of sources of error between 2 popular segmental body composition techniques and facilitate interpretation of estimates from these technologies.

Trunk pitch oscillations for energy trade-offs in bipedal running birds and robots

Bipedal animals have diverse morphologies and advanced locomotion abilities. Terrestrial birds, in particular, display agile, efficient, and robust running motion, in which they exploit the interplay between the body segment masses and moment of inertias. On the other hand, most legged robots are not able to generate such versatile and energy-efficient motion and often disregard trunk movements as a means to enhance their locomotion capabilities. Recent research investigated how trunk motions affect the gait characteristics of humans, but there is a lack of analysis across different bipedal morphologies. To address this issue, we analyze avian running based on a spring-loaded inverted pendulum model with a pronograde (horizontal) trunk. We use a virtual point based control scheme and modify the alignment of the ground reaction forces to assess how our control strategy influences the trunk pitch oscillations and energetics of the locomotion. We derive three potential key strategies to leverage trunk pitch motions that minimize either the energy fluctuations of the center of mass or the work performed by the hip and leg. We suggest how these strategies could be used in legged robotics.

The Effects of Personalized Versus Generic Scaling of Body Segment Masses on Joint Torques During Stationary Wheelchair Racing.

The anthropometries of elite wheelchair racing athletes differ from the generic, able-bodied anthropometries commonly used in computational biomechanical simulations. The impact of using able-bodied parameters on the accuracy of simulations involving wheelchair racing is currently unknown. In this study, athlete-specific mass segment inertial parameters of the head and neck, torso, upper arm, forearm, hand, thigh, shank, and feet for five elite wheelchair athletes were calculated using dual-energy X-ray absorptiometry (DXA) scans. These were compared against commonly used anthropometrics parameters of data presented in the literature. A computational biomechanical simulation of wheelchair propulsion using the upper extremity dynamic model in opensim assessed the sensitivity of athlete-specific mass parameters using Kruskal-Wallis analysis and Spearman correlations. Substantial between-athlete body mass distribution variances (thigh mass between 7.8% and 22.4% total body mass) and between-limb asymmetries (<62.4% segment mass; 3.1 kg) were observed. Compared to nonathletic able-bodied anthropometric data, wheelchair racing athletes demonstrated greater mass in the upper extremities (up to 3.8% total body mass) and less in the lower extremities (up to 9.8% total body mass). Computational simulations were sensitive to individual body mass distribution, with joint torques increasing by up to 31.5% when the scaling of segment masses (measured or generic) differed by up to 2.3% total body mass. These data suggest that nonathletic, able-bodied mass segment inertial parameters are inappropriate for analyzing elite wheelchair racing motion.

Elders’ fall detection based on biomechanical features using depth camera

An accidental fall poses a serious threat to the health of the elderly. With the advances of technology, an increased number of surveillance systems have been installed in the elderly home to help medical staffs find the elderly at risk. Based on the study of human biomechanical equilibrium, we proposed a fall detection method based on 3D skeleton data obtained from the Microsoft Kinect. This method leverages the accelerated velocity of Center of Mass (COM) of different body segments and the skeleton data as main biomechanical features, and adopts Long Short-Term Memory networks (LSTM) for fall detection. Compared with other fall detection methods, it does not require older people to wear any other sensors and can protect the privacy of the elderly. According to the experiment to validate our method using the existing database, we found that it could efficiently detect the fall behaviors. Our method provides a feasible solution for the fall detection that can be applied at homes of the elderly.

Biomimetics of throwing at basketball

The paper deals with the inverse dynamics of a kinematic chain of the human upper limb when throwing the ball at the basketball, aiming to calculate the torques required to put in action the technical system. The kinematic chain respects the anthropometric features regarding the length and mass of body segments. The kinematic parameters of the motion were determined by measuring the angles of body segments during a succession of filmed pictures of a throw, and the interpolation of these values and determination of the interpolating polynomials for each independent geometric coordinate. Using the Lagrange equations, there were determined the variations with time of the required torques to put in motion the kinematic chain of the type of triple physical pendulum. The obtained values show, naturally, the fact that the biggest torque is that for mimetic articulation of the shoulder, being comparable with those obtained by the brachial biceps muscle of the analyzed human subject. Using the obtained data, there can be conceived the mimetic technical system, of robotic type, with application in sports, so that to perform the motion of ball throwing, from steady position, at the basket.

Body segment parameters of Paralympic athletes from dual-energy X-ray absorptiometry

This research represents the first documented investigation into the body segment parameters of Paralympic athletes (e.g., individuals with spinal cord injuries and lower extremity amputations). Two-dimensional body segment parameters (i.e., mass, length, position vector of the center of mass, and principal mass moment of inertia about the center of mass) were quantified from dual-energy X-ray absorptiometry (DXA). In addition to establishing a body segment parameter database of Paralympic athletes for prospective biomechanists and engineers, the mass of each body segment as experimentally measured via the DXA imaging was compared with that reported by previous research of able-bodied cadavers. In general, there were significant differences in the body segment masses between the different methods. These findings support the implementation of the proposed database for developing valid multibody biomechanical models of Paralympic athletes with distinct physical disabilities.

Compressive and shear hip joint contact forces are affected by pediatric obesity during walking

Obese children exhibit altered gait mechanics compared to healthy-weight children and have an increased prevalence of hip pain and pathology. This study sought to determine the relationships between body mass and compressive and shear hip joint contact forces during walking. Kinematic and kinetic data were collected during treadmill walking at 1ms−1 in 10 obese and 10 healthy-weight 8–12 year-olds. We estimated body composition, segment masses, lower-extremity alignment, and femoral neck angle via radiographic images, created personalized musculoskeletal models in OpenSim, and computed muscle forces and hip joint contact forces. Hip extension at mid-stance was 9° less, on average, in the obese children (p<0.001). Hip abduction, knee flexion, and body-weight normalized peak hip moments were similar between groups. Normalized to body-weight, peak contact forces were similar at the first peak and slightly lower at the second peak between the obese and healthy-weight participants. Total body mass explained a greater proportion of contact force variance compared to lean body mass in the compressive (r2=0.89) and vertical shear (perpendicular to the physis acting superior-to-inferior) (r2=0.84) directions; lean body mass explained a greater proportion in the posterior shear direction (r2=0.54). Stance-average contact forces in the compressive and vertical shear directions increased by 41N and 48N, respectively, for every kilogram of body mass. Age explained less than 27% of the hip loading variance. No effect of sex was found. The proportionality between hip loads and body-weight may be implicated in an obese child׳s increased risk of hip pain and pathology.

Quantifying Body Segment Parameters Using Dual-Energy X-Ray Absorptiometry: A Paralympic Wheelchair Curler Case Report

The body segment parameters of a Paralympic wheelchair curler were experimentally investigated; the athlete has an incomplete cervical spinal cord injury. Two-dimensional body segment parameters (i.e., mass, length, position vector of the center of mass, and principal mass moment of inertia about the center of mass) were quantified using dual-energy x-ray absorptiometry (DXA). In addition to measuring the body segment parameters in the interest of developing a subject-specific multibody biomechanical model, the mass of each body segment as experimentally measured via the DXA imaging was compared with that reported by previous research of able-bodied cadavers. In general, there were significant differences in the body segment masses between the different methods. The composition of each body segment (i.e., percentage of skeletal muscle, bone mineral content, and adipose tissue) was additionally investigated.

Modeling of human model for static pressure distribution prediction

Vehicle comfort, the key factor that influences the purchase of automobile products, is becoming increasingly important. However, the processes of traditional empirical and experimental approaches to design a new, more comfortable seat is complicated, time consuming and costly. The finite element method could facilitate, accelerate and economize this process. In the present work, a complete human FE model is established based on the Hybrid III dummy, the appropriate element size of 10 mm was ascertained. The body segment mass was verified by comparing segment mass percentages obtained from this model with previous data. The further validation study of the human model was achieved via the human pressure distribution experiments over human-rigid seat interaction under three postures, the validation reveals that the simulation results agree well with the experimental data. On this basis, the human model was applied to predict the interactions between human body and an automobile seat, then the contact pressure distribution, additional information about the contact shear stresses distribution and stress distribution within the soft tissue were obtained through simulation. The human model presented in this paper can reflect the interaction between human body and automobile seat precisely. Relevance to industryThe results deduced that the model is capable of realistically predicting pressure distribution, the present model allows the evaluation of seating comforts in a virtual phase of seat development, and the study can be taken as reference for vehicle seat design and biomechanical evaluation.

Alignment of centers of mass of body segments with the gravity line

Sagittal malalignment is associated with increased disability and can lead to postural troubles. The latter is often the result of an inadequate weight distribution on the spine and trigger compensatory mechanisms. No study to date has provided reference values for the alignment of centers of mass (CoM) of different body segments in asymptomatic subjects. The use of a bi-planar X-ray system (Dubousset et al. 2010) combined with 3D reconstruction of the external body shape (Nerot et al. 2015) allows for computation of the body segments’ CoM. The aim of this study was to provide baseline values for the position of each segment’s CoM compared to the gravity line (GL) in the sagittal plane.

Mass-inertial Parameters of the Human Thigh Based on Data for Bulgarian Males: Three-dimensional Mathematical Model Study

The estimation of body segment parameters is important for humanmotion analysis and many biomechanical activities. For studying these aprecise modeling of the individual segments of the body is necessary. The aim of this work is to improve the geometric modeling of the human thigh of the Bulgarian males, taking into account that the segment is dissect from the torso with a plane passing through the anterior superior iliacspine at an angle of 37 degrees to the sagittal plane. In our previous studythe thigh was modeled as a frustum of cone. In the current study thethigh is modeled with geometric body being a combination of a frustumof circular cone on top of which is placed a part of cylinder cut with aplane making angle of 53 with respect to its base. This second part ex-tends from anthropometric points omphalion - iliospinale. Modeling of thebody segments by means of simple geometrical bodies enforces a seriousapproximation of their shape and, therefore, of their volume and relatedcharacteristics as mass and moments of inertia. Hence, adjustment of themeasured geometrical parameters that would produce the best approxima-tion of the body segment mass characteristics is highly desirable. This canbe done by using the regression mass equations derived in Zatsiorsky andSeluyanov and Shan and Bohn. Yet, by doing so we avoid deviations ofthe adjusted parameters from the measured values, larger than 10%. Wederive analytically and estimate numerically the volume, mass, the positionof the center of mass and moments of inertia of the thigh and compare theseresults with the ones available from the literature for other Caucasian.

Quantitative analysis of skeletal muscle mass in patients with rheumatic diseases under glucocorticoid therapy – Comparison among bioelectrical impedance analysis, computed tomography, and magnetic resonance imaging

Objectives. To determine the availability of bioelectrical impedance analysis (BIA), computed tomography (CT), and magnetic resonance imaging (MRI) for measurement of skeletal muscle mass in patients with rheumatic diseases and quantitatively assess skeletal muscle loss after glucocorticoid (GC) treatment.Methods. The data from 22 patients with rheumatic diseases were retrospectively obtained. The muscle mass of body segments was measured with a BIA device in terms of skeletal muscle mass index (SMI). Cross-sectional area (CSA) was obtained from CT and MRI scans at the mid-thigh level using the image analysis program. We further assessed the data of three different measurements before and after GC treatment in 7 patients with rheumatic diseases.Results. SMI of whole body was significantly correlated with estimated muscle volume and mid-thigh muscle CSA with CT and MRI (p < 0.01). Significant correlations between SMI and mid-thigh muscle CSA of each leg were also found (p < 0.01). All the three measurements were negatively correlated with GC dosage (p < 0.01). Significant decline in mid-thigh muscle CSA with CT and MRI was found after GC treatment in 7 patients (p < 0.02). Those patients showed significant decline in SMI of whole body after GC treatment, but not in SMI of each leg. On the other hand, significant correlations between mid-thigh muscle CSA with CT and MRI were found before and after GC treatment (p < 0.01).Conclusions. GC-related skeletal muscle loss could be quantitatively assessed with BIA, CT, or MRI in patients with rheumatic diseases, and CT and MRI appeared to be more accurate than BIA.