Real Body Shape Research Articles

Which Body Would You Like to Have? The Impact of Embodied Perspective on Body Perception and Body Evaluation in Immersive Virtual Reality.

In this experiment, we aimed to measure the conscious internal representation of one's body appearance and allow the participants to compare this to their ideal body appearance and to their real body appearance. We created a virtual representation of the internal image participants had of their own body shape. We also created a virtual body corresponding to the internal representation they had of their ideal body shape, and we built another virtual body based on their real body measures. Participants saw the three different virtual bodies from an embodied first-person perspective and from a third-person perspective and had to evaluate the appearance of those virtual bodies. We observed that female participants evaluated their real body as more attractive when they saw it from a third-person perspective, and that their level of body dissatisfaction was lower after the experimental procedure. We believe that third-person perspective allowed female participants to perceive their real body shape without applying the negative prior beliefs usually associated to the “self”, and that this resulted in a more positive evaluation of their body shape. We speculate that this method could be applied with patients suffering from eating disorders, by making their body perception more realistic and therefore improve their body satisfaction.

In-silico pre-clinical trials are made possible by a new simple and comprehensive lumbar belt mechanical model based on the Law of Laplace including support deformation and adhesion effects.

Lower back pain is a major public health problem. Despite claims that lumbar belts change spinal posture due to applied pressure on the trunk, no mechanical model has yet been published to prove this treatment. This paper describes a first model for belt design, based on the one hand on the mechanical properties of the fabrics and the belt geometry, and on the other hand on the trunk geometrical and mechanical description. The model provides the estimation of the pressure applied to the trunk, and a unique indicator of the belt mechanical efficiency is proposed: pressure is integrated into a bending moment characterizing the belt delordosing action on the spine. A first in-silico clinical study of belt efficiency for 15 patients with 2 different belts was conducted. Results are very dependent on the body shape: in the case of high BMI patients, the belt effect is significantly decreased, and can be even inverted, increasing the lordosis. The belt stiffness proportionally increases the pressure applied to the trunk, but the influence of the design itself on the bending moment is clearly outlined. Moreover, the belt/trunk interaction, modeled as sticking contact and the specific way patients lock their belts, dramatically modifies the belt action. Finally, even if further developments and tests are still necessary, the model presented in this paper seems suitable for in-silico pre-clinical trials on real body shapes at a design stage.

Spatiotemporal Feedback and Network Structure Drive and Encode Caenorhabditis elegans Locomotion.

Using a computational model of the Caenorhabditis elegans connectome dynamics, we show that proprioceptive feedback is necessary for sustained dynamic responses to external input. This is consistent with the lack of biophysical evidence for a central pattern generator, and recent experimental evidence that proprioception drives locomotion. The low-dimensional functional response of the Caenorhabditis elegans network of neurons to proprioception-like feedback is optimized by input of specific spatial wavelengths which correspond to the spatial scale of real body shape dynamics. Furthermore, we find that the motor subcircuit of the network is responsible for regulating this response, in agreement with experimental expectations. To explore how the connectomic dynamics produces the observed two-mode, oscillatory limit cycle behavior from a static fixed point, we probe the fixed point’s low-dimensional structure using Dynamic Mode Decomposition. This reveals that the nonlinear network dynamics encode six clusters of dynamic modes, with timescales spanning three orders of magnitude. Two of these six dynamic mode clusters correspond to previously-discovered behavioral modes related to locomotion. These dynamic modes and their timescales are encoded by the network’s degree distribution and specific connectivity. This suggests that behavioral dynamics are partially encoded within the connectome itself, the connectivity of which facilitates proprioceptive control.

Mass flow stability method in the extraction process calculations

Mass flow stability method, allowing to clarify the existing analytical dependences for calculating the target component withdrawal from the classical-shape bodies (unlimited plate, cylinder, sphere) was proposed. On the example of the III class bodies, application of the method is shown. A mathematical model of the target component extraction from the round particle was developed and the dependence to calculate the concentration was obtained. Consideration of the real body shape deviations from perfect in the form of the shape factor allows to refine the design value for the bodies, corresponding to the III class. It was found that the deviation of the concentration values for the perfect body from real would be the greater, the smaller the particle radius. The maximum relative error of calculations is 11.3 %. It is shown that the target component extraction process is rather complicated and depends strongly on a large number of defining physical characteristics: particle size, diffusion coefficient, mass transfer coefficient, temperature, duration.

Mathematical model of heat transfer during the extraction of particles of ideal (spherical) and real forms

Mass flow stability method, allowing to clarify the existing analytical dependences for calculating the target component withdrawal from the classical-shape bodies (unlimited plate, cylinder, sphere) was proposed. On the example of the III class bodies, application of the method is shown. A mathematical model of the target component extraction from the round particle was developed and the dependence to calculate the concentration was obtained. Consideration of the real body shape deviations from perfect in the form of the shape factor allows to refine the design value for the bodies, corresponding to the III class. It was found that the deviation of the concentration values for the perfect body from real would be the greater, the smaller the particle radius. The maximum relative error of calculations is 11.3%. It is shown that the target component extraction process is rather complicated and depends strongly on a large number of defining physical characteristics: particle size, diffusion coefficient, mass transfer coefficient, temperature, duration.

Creating real body model of dressed human based on fat extent of body

The paper presents a method to estimate real body shape of dressed human. In the method we build a function to describe the fat extent of every vertex on the body. The fat extent is relative to the slim body template and the fat body template. Using the fat function and two templates a synthesizing model is created. The 3D scans of dressed human obtained by kinects are used to calculate the fat extents of feature rings on the bodies, and the results are used as the control points to build the fat function. We construct two databases corresponding to the persons wearing winter clothes and summer clothes respectively. The two databases consist of the fat extents of the feature rings on the naked bodies and on the 3D scans of dressed human. According the current season and the corresponding database, considering the proportional relations about these feature rings' fat extents as restrictions, the real body of dressed human can be estimated with quadratic programming. The experiments demonstrate the availability of our method.

Posture and depth adjustable 3D body model for individual pattern making

PurposeThis paper aims to describe the development of an interactive body model that can be altered to match individual body perimeter, postures and depth for the purpose of computerized pattern making.Design/methodology/approachConstruction of the posture and depth adjustable body model requires the extraction of ten points, adjustment of coordinate points, linking of points by spline curves, control of section lengths and selectability of three hip types. Front to back depth of the model is adjusted by scaling ratio.FindingsGood results were achieved in modelling back shapes, such as flat shape and stoop shape, and of modelling various hip shapes, such as flat shape and protruding shape. Also the presented body model is able to accurately simulate individual depth of bust, waist and hips. Silhouette comparison between the fully adjusted virtual body model and real body shapes shows an almost perfect match. A primary dialog for altering perimeter, length and depth, and a posture dialog for controlling back and hip shapes was developed.Originality/valueBy making fine adjustments to posture and depth, it is possible to make patterns which result in clothing that not only fits well, but also exhibits other desirable properties. This system could, therefore, be seen as a major step forward in pattern making.