Sensitivity of subject-specific upper body musculoskeletal model predictions to mass scaling methods.

Accurate predictions of spinal loads in subject-specific musculoskeletal models require precise body segment parameters, including segment mass and center of mass (CoM) locations. Existing upper body models often assume a constant percentage of total body mass to calculate segmental masses, disregarding inter-individual variability and limiting their predictive capacity. This study evaluated the sensitivity of subject-specific upper body musculoskeletal model predictions to body mass scaling methods. The upper body segmental masses and corresponding CoM of six male subjects with varying body mass indices were computed using two mass scaling methods: the constant-percentage-based (CPB) scaling method, commonly used in AnyBody software; and our recently developed body-shape-based (BSB) method. Subsequently, these values were used by a validated musculoskeletal model to predict the muscle and disc forces in upright and flexed postures. The discrepancies between the results of the two scaling methods were compared across subjects and postures. Maximum deviations in thorax masses reached up to 7.5% of total body weight (TBW) in overweight subjects, while maximum CoM location differences of up to 35 mm were observed in normal weight subjects. The root mean squared errors (RMSE) of the CPB results, calculated with the BSB results as baseline, showed that the muscle and shear forces of the two scaling methods were quite similar (<4.5% of TBW). Though, there were small to moderate differences in compressive forces (6.5-16.0% of TBW). Thus, the compressive forces predicted with CPB method should be used with caution, particularly for overweight and obese subjects.

Prediction of human male trunk mass distribution using anthropometric measurements: A feasibility study.

The current study proposes a new method to predict the body shape and mass distribution of the trunk (Tl-L5) of a human male using 15 anthropometric measurements acquired at various locations of the body. Trunk cross-sectional images adopted from the Visible Human male project database were segmented into fat, bone, and lean tissue. Assuming that all male subjects have similar cross-sectional composition at a given body height percentile, areas of the segmented cross-sectional images of the Visible Human male along the trunk were scaled to match those of the predicted body shape. The trunk mass distribution of the target subject can then be computed using the density values of fat, bone, and lean tissue. Comparison of the predicted body shape circumference with ground truth values measured using digital and actual measurements yielded maximum mean error of 13.3 mm and 30.3 mm, respectively. The accuracy of the image segmentation was evaluated, and the results showed a high Jaccard index (>0.95). The proposed method was able to predict the trunk mass distribution of two volunteers with a maximum deviation of 384 g at T4 level and a minimum deviation of 12 g at L4 level and the corresponding centers of mass fell within the experimental data at most levels. Thus, our method can be considered as a feasible option to calculate subject-specific trunk mass distribution.

A Literature Review: Geometric Methods and Their Applications in Human-Related Analysis.

Geometric features, such as the topological and manifold properties, are utilized to extract geometric properties. Geometric methods that exploit the applications of geometrics, e.g., geometric features, are widely used in computer graphics and computer vision problems. This review presents a literature review on geometric concepts, geometric methods, and their applications in human-related analysis, e.g., human shape analysis, human pose analysis, and human action analysis. This review proposes to categorize geometric methods based on the scope of the geometric properties that are extracted: object-oriented geometric methods, feature-oriented geometric methods, and routine-based geometric methods. Considering the broad applications of deep learning methods, this review also studies geometric deep learning, which has recently become a popular topic of research. Validation datasets are collected, and method performances are collected and compared. Finally, research trends and possible research topics are discussed.

Interactor's body shape does not affect visuo-motor interference effects during motor coordination.

The biological-tuning of the Action Observation Network is highly debated. A current open question relates to whether the morphological appearance (body shape) and/or the biological motion of the observed agent triggers action simulation processes. Motor simulation of the partner's action is critical for motor interactions, where two partners coordinate their actions in space and time. It supports interpersonal alignment and facilitates online coordination. However, motor simulation also leads to visuo-motor interference effects when people are required to coordinate with complementary actions, i.e. incongruent movements as compared to the observed ones. Movement kinematics of interactive partners allows us to capture their automatic tendency to simulate and imitate the partner's complementary movements. In an online reach-to-grasp task, we investigated whether visuo-motor interference effects, visible in the kinematics of complementary movements, are modulated by the visual presence of the interactor's body shape. We asked participants to interact with 1) a humanoid agent with a human-like body shape and with real human, biological, movement kinematics, or 2) a non-humanoid agent, which did not resemble the human body-shape but moved with the same real kinematics. Through the combination of inferential and Bayesian statistics, the results show no effect of interactor's body shape on visuo-motor interference in reaching and grasping kinematics during online motor coordination. We discuss the results and propose that the kinematics of the observed movements, during motor interactions, might be the key factor for visuo-motor interference to take place independently from the morphological appearance of the partner. This is particularly relevant in a technological society that constantly asks humans to interact with artificial agents.

Evaluation of the Wearing Characteristics of Hip Protectors Based on Draping Pattern Design and Body Shape in Korean Elderly People

PURPOSE: The purpose of this study was to verify the new hip protector design with respect to the comfort and mobility. The new hip protector was developed based on a pattern of draping and body shape of Korean elderly individuals. MATERIALS AND METHODS: An wearing characteristics evaluation was conducted on 101 elderly women wearing hip protector using a questionnaire of preference and ease of wearing. Hip protectors, with existing and newly developed belt and underwear types, which were previously preferred by the Korean elderly, were evaluated. RESULTS: The newly developed belt type (65.0%) and newly developed underwear type (30.1%) hip protectors were preferred to the existing type (3.9%) and existing underwear type (1.0%) ones. The convenience of the newly developed belt type was greater than 4 out of 5 points (1 for strongly disagree and 5 for strongly agree) for all nine measures, including fit, allowance, mobility, pad placement, pad thickness, pad size, material, design, ease of dressing, and ease of undressing. The newly developed hip protectors showed less discomfort than the existing ones. In particular, the newly developed belt type and developed underwear type improved sitting convenience by 31.1% and 26.1%, respectively, compared with the existing ones. CONCLUSION: The hip protectors developed in the present study is expected to provide better fit for the body shape of Korean elderly individuals and prevent hip fracture due to fall.