Improved Calculation Method of Coupling Factors for Low-Frequency Wireless Power Transfer Systems

The concept of a coupling factor was introduced in International Electrotechnical Commission (IEC) 62311 and 62233 to provide a product safety assessment that considers the localized exposure when an electromagnetic field (EMF) source is close to the human body. To calculate the coupling factors between the human body and EMF source, a numerical calculation should be carried out to calculate the internal quantities of the human body models. However, at frequencies below 10 MHz, the computed current density or internal electric field has computational artifacts from segmentation or discretization errors. Specifically, coupling factors are calculated based on the maximum values, which may include computational artifacts due to abnormal peaks. In this study, we propose an improved calculation method to remove computational artifacts by applying the 99.99th percentile in calculating the coupling factors without underestimation. The performance of the proposed method is verified through a comparison based on various human body models with wireless power transfer (WPT) systems and compliance with the reference levels and basic restrictions. The results indicate that the proposed method can provide uniform coupling factors by reducing the computational errors by up to 65.3% compared to a conventional method.

Kinetic and Kinematic Features of Pedestrian Avoidance Behavior in Motor Vehicle Conflicts

The active behaviors of pedestrians, such as avoidance motions, affect the resultant injury risk in vehicle–pedestrian collisions. However, the biomechanical features of these behaviors remain unquantified, leading to a gap in the development of biofidelic research tools and tailored protection for pedestrians in real-world traffic scenarios. In this study, we prompted subjects (“pedestrians”) to exhibit natural avoidance behaviors in well-controlled near-real traffic conflict scenarios using a previously developed virtual reality (VR)-based experimental platform. We quantified the pedestrian–vehicle interaction processes in the pre-crash phase and extracted the pedestrian postures immediately before collision with the vehicle; these were termed the “pre-crash postures.” We recorded the kinetic and kinematic features of the pedestrian avoidance responses—including the relative locations of the vehicle and pedestrian, pedestrian movement velocity and acceleration, pedestrian posture parameters (joint positions and angles), and pedestrian muscle activation levels—using a motion capture system and physiological signal system. The velocities in the avoidance behaviors were significantly different from those in a normal gait (p < 0.01). Based on the extracted natural reaction features of the pedestrians, this study provides data to support the analysis of pedestrian injury risk, development of biofidelic human body models (HBM), and design of advanced on-vehicle active safety systems.

Dynamic Spatial Tuning Patterns of Shoulder Muscles with Volunteers in a Driving Posture

Computational human body models (HBMs) of drivers for pre-crash simulations need active shoulder muscle control, and volunteer data are lacking. The goal of this paper was to build shoulder muscle dynamic spatial tuning patterns, with a secondary focus to present shoulder kinematic evaluation data. 8M and 9F volunteers sat in a driver posture, with their torso restrained, and were exposed to upper arm dynamic perturbations in eight directions perpendicular to the humerus. A dropping 8-kg weight connected to the elbow through pulleys applied the loads; the exact timing and direction were unknown. Activity in 11 shoulder muscles was measured using surface electrodes, and upper arm kinematics were measured with three cameras. We found directionally specific muscle activity and presented dynamic spatial tuning patterns for each muscle separated by sex. The preferred directions, i.e. the vector mean of a spatial tuning pattern, were similar between males and females, with the largest difference of 31° in the pectoralis major muscle. Males and females had similar elbow displacements. The maxima of elbow displacements in the loading plane for males was 189 ± 36 mm during flexion loading, and for females, it was 196 ± 36 mm during adduction loading. The data presented here can be used to design shoulder muscle controllers for HBMs and evaluate the performance of shoulder models.

Personalized Clothing Design Support System for Special Crowds Based on Artificial Intelligence Technology

In today’s society, people’s demand for personalized clothing is increasing, and they are increasingly pursuing traditional elements. Therefore, many fashion designers will incorporate folk elements into the traditional clothing design concepts to meet this demand. Sc a kind of computer technology Personalized auxiliary design software is produced. The function of this software is to use the MVC architecture to create system function modules, and then use the Kinect-based three-dimensional scanning system to model the human body, so as to clearly understand and obtain human body models with different characteristics. Take the folk art elements of opera as an example, integrate the opera elements into the costume design and save it in the database of the system. Under the action of the virtual algorithm, the personalized costume is matched with the human body model, which completes the costume design. Personalized design, and better design results can be obtained through this auxiliary design software.

Personalization of a Human Body Model Using Subject-Specific Dimensions for Designing Clothing Patterns

Virtual human body models contribute to designing safe and user-friendly products through virtual prototyping. Anthropometric biomechanical models address different physiques using average dimensions. In designing, e.g., personal protective equipment, orthopedic tools, or vehicle safety systems, biomechanical models with the correct geometry and shape shall play a role. The presented study shows the variations of subject-specific anthropometric dimensions from the average of the different population groups in the Czech Republic and China as a background for the need for personalized human body models. The study measures a set of dimensions used to design clothing patterns of Czech children, Czech adolescents, Czech adults, and Chinese adults and compares them to the corresponding age average, which is represented by a scaled anthropometric human body model. The cumulative variation of the dimensions used to design the clothing patterns increases the further the population group is from the average. It is smallest for the Czech adults at 7.54 ± 6.63%; Czech adolescents report 7.93 ± 6.25%; Czech children differ be 9.52 ± 6.08%. Chinese adults report 10.86 ± 11.11%. The variations from the average of the particular dimensions used to design clothing patterns prove the necessity of having personalized subject-specific models. The measured dimensions used to design the clothing patterns serve as the personalization of particular body segments and lead to a subject-specific virtual model. The developed personalization algorithm results in the continuous body surface desired for contact applications for assessing body behavior and injury risk under impact loading.

Personalization of a Human Body Model Using Subject-Specific Clothing Industry Dimensions

Virtual human body models contribute to designing safe and user-friendly products through virtual prototyping. Anthropometric biomechanical models address different physiques using average dimensions. In designing personal protective equipment, biomechanical models with the correct geometry and shape shall play a role. The presented study shows the variations of subject-specific anthropometric dimensions from the average for the different population groups in the Czech Republic and China as a background for the need for personalized human body models. The study measures a set of clothing industry dimensions of Czech children, Czech teens, Czech adults and Chinese adults and compares them to the corresponding age average, which is represented by a scaled anthropometric human body model. The cumulative variation of clothing industry dimensions increases the farer is the population group from the average. It is smallest for the Czech adults 7.54% ± 6.63%, Czech teens report 7.93% ± 6.25% and Czech children differ 9.52% ± 6.08%. Chinese adults report 10.86% ± 11.11%. As the variations of the particular clothing industry dimensions from the average prove the necessity of having personalized subject-specific models, the personalization of particular body segments using the measured clothing industry dimensions leading to a subject-specific virtual model is addressed. The developed personalization algorithm results in the continuous body surface desired for contact applications for assessing body behavior and injury risk under impact loading.

Detailed 3D human body reconstruction from multi-view images combining voxel super-resolution and learned implicit representation

The task of reconstructing detailed 3D human body models from images is interesting but challenging in computer vision due to the high freedom of human bodies. This work proposes a coarse-to-fine method to reconstruct detailed 3D human body from multi-view images combining Voxel Super-Resolution (VSR) based on learning the implicit representation. Firstly, the coarse 3D models are estimated by learning an Pixel-aligned Implicit Function based on Multi-scale Features (MF-PIFu) which are extracted by multi-stage hourglass networks from the multi-view images. Then, taking the low resolution voxel grids which are generated by the coarse 3D models as input, the VSR is implemented by learning an implicit function through a multi-stage 3D convolutional neural network. Finally, the refined detailed 3D human body models can be produced by VSR which can preserve the details and reduce the false reconstruction of the coarse 3D models. Benefiting from the implicit representation, the training process in our method is memory efficient and the detailed 3D human body produced by our method from multi-view images is the continuous decision boundary with high-resolution geometry. In addition, the coarse-to-fine method based on MF-PIFu and VSR can remove false reconstructions and preserve the appearance details in the final reconstruction, simultaneously. In the experiments, our method quantitatively and qualitatively achieves the competitive 3D human body models from images with various poses and shapes on both the real and synthetic datasets.

Analysis of individual differences in pelvic and spine alignment in seated posture and impact on the seatbelt kinematics using human body model

Analysis using human body models has been performed to reduce the impact of accidents; however, no analysis has shown a relationship between lumbar and pelvic/spine angle and seat belts in reducing human damage from accidents. Lumbar and pelvic/spine angles were measured in 75 individuals and the measurements were used to create three different angles for the Total Human Model for Safety model. In the present study, we focused on lumber lordosis (LL) and pelvic angle (PA). A normal distribution and histogram were used for analysis of PA (01, 10, and 50). The Total Human Model for Safety, including LL and PA, was corrected using finite element software. Simulations were conducted under the conditions of the Japan New Car Assessment Programme (JNCAP) 56 kph full lap frontal impact. Using the results of the FEM, the amount of lap-belt cranial sliding-up, anterior movement of the pelvis, posterior tilt of the pelvis, head injury criterion (HIC), second cervical vertebrae (C2) compressive load, C2 moment, chest deflectiou (upper, middle, and lower), left and right femur load, and shoulder belt force were measured. The lap-belt cranial sliding-up was 1.91 and 2.37 for PA10 and PA01, respectively, compared to PA50; the anterior movement of the pelvis was 1.08 and 1.12 for PA10 and PA01, respectively; and the posterior tilt of the pelvis was 1.1 and 1.18 for PA10 and PA01, respectively. HIC was 1.13 for PA10 and 1.58 for PA01; there was no difference in C2 compressive load by PA, but C2 moment increased to 1.59 for PA10 and 2.72 for PA01. It was found that as LL increases and the PA decreases, the seat belt becomes likely to catch the iliac bone, making it harder to cause injury. This study could help to reconsider the safe seat and seatbelt position in the future.

How muscle stiffness affects human body model behavior

Background Active human body models (AHBM) consider musculoskeletal movement and joint stiffness via active muscle truss elements in the finite element (FE) codes in dynamic application. In the latest models, such as THUMS™ Version 5, nearly all human muscle groups are modeled in form of one-dimensional truss elements connecting each joint. While a lot of work has been done to improve the active and passive behavior of this 1D muscle system in the past, the volumetric muscle system of THUMS was modeled in a much more simplified way based on Post Mortem Human Subject (PMHS) test data. The stiffness changing effect of isometric contraction was hardly considered for the volumetric muscle system of whole human body models so far. While previous works considered this aspect for single muscles, the effect of a change in stiffness due to isometric contraction of volumetric muscles on the AHBM behavior and computation time is yet unknown. Methods In this study, a simplified frontal impact using the THUMS Version 5 AM50 occupant model was simulated. Key parameters to regulate muscle tissue stiffness of solid elements in THUMS were identified for the material model MAT_SIMPLIFIED_FOAM and different stiffness states were predefined for the buttock and thigh. Results During frontal crash, changes in muscle stiffness had an effect on the overall AHBM behavior including expected injury outcome. Changes in muscle stiffness for the thigh and pelvis, as well as for the entire human body model and for strain-rate-dependent stiffness definitions based on literature data had no significant effect on the computation time. Discussion Kinematics, peak impact force and stiffness changes were in general compliance with the literature data. However, different experimental setups had to be considered for comparison, as this topic has not been fully investigated experimentally in automotive applications in the past. Therefore, this study has limitations regarding validation of the frontal impact results. Conclusion Variations of default THUMS material model parameters allow an efficient change in stiffness of volumetric muscles for whole AHBM applications. The computation time is unaffected by altering muscle stiffness using the method suggested in this work. Due to a lack of validation data, the results of this work can only be validated with certain limitations. In future works, the default material models of THUMS could be replaced with recently published models to achieve a possibly more biofidelic muscle behavior, which would even allow a functional dependency of the 1D and 3D muscle systems. However, the effect on calculation time and model stability of these models is yet unknown and should be considered in future studies for efficient AHBM applications.