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Zoning design of pressure comfort of women's shaping pants is studied in this paper based on the new material made by the LRJ40/1F warp-knitting machine.

According to the distribution of body fat and the pressure comfort range of the shaping pants, zoning design is carried out. The pressure comfort of the women's shaping pants is tested by the objective pressure test and the subjective evaluation method.

The result is that using the method of zoning design can satisfy the comfort of the lower limbs while improving the mobility and plasticity.

Pressure comfort has become an important index to evaluate the comfort of elastic shaping pants. However, there were very few studies on the relationship between the pressure comfort of warp-knitted elastic pants and the design of jacquard organization in China and abroad.

The purpose of this paper is to find out the main factors that influence wearing comfort and how they influence garment-wearing comfort.

Overall, 120 postures were extracted from the activities of daily life and work. Then, the numerical values of clothing pressure of these postures were measured using three-dimension virtual-reality technology. Finally, the data mining technology was applied to analyze the collected data.

The wearing comfort of pants is mainly influenced by four factors – waist-hip factor, knee-shank factor, crotch factor and thigh-calf factor – and their contributions account for 39.17, 16.4, 13.96 and 6.95 percent, respectively. Hip, waist, crotch and knee influence wearing comfort significantly, and the part below the knee and the part of back thigh have no obvious effect on wearing comfort. Furthermore, the wearing comfort is acceptable if the numerical clothing pressures are below 20 kPa at the parts of hip, waist and crotch and below 10 kPa at the parts of back thigh, knee and shank.

The paper demonstrates how different human body parts influence garment-wearing comfort. All of the results in this research facilitate pattern design of pants and quantitative evaluation of garment-wearing comfort.

Currently, the researches on garment development and wear comfort evaluation mainly focus on the static condition type and seldom involved dynamic condition. Therefore, the purpose of this paper is to develop cycling clothes’ patterns and evaluate their dynamic wear comfort.

First, the 3D-to-2D flattening technology was applied to develop garment patterns of a cycler’s jersey T-shirt. Then, 3D animation technology was used to simulate the scene of cycling. Next, a novel pressure-measuring method was proposed to measure static and dynamic clothing pressures in a virtual environment. Finally, the collected data were used for evaluating wear comfort.

Compared to static conditions, the dynamic wear comfort noticeably improved at the front neck, side neck, upper front chest, around back neck point and front shoulder, and the front neck. Compared to static conditions, the dynamic wear comfort visibly deteriorates at the back neck, below chest, outseam, back except around back neck point and around scapula, and the around scapula area. The dynamic pressure at back neck, below front chest and shoulder fluctuate wildly throughout the whole cycling. On the contrary, the dynamic pressure at the front neck, side neck, front upper chest and at the back cause it to tend to stability during cycling.

The 3D virtual-reality technology was applied to simulate cycling. And a novel method was proposed to measure numerical clothing pressures for evaluating the dynamic wear comfort. The proposed method can not only quantitatively evaluate the wear comfort of cycling clothes and optimize cycling clothes’ patterns, but also can be applied to other tight garment types.

The purpose of this paper is to clarify the relationship between dynamic clothing pressure of women's sports bras and heart rate variation indexes during playing basketball.

Totally, 35 healthy females aged between 20 and 24 were employed as subjects. Their heart rate variability (HRV) data and the clothing pressure values when wearing sports bras of different bust sizes during playing basketball were measured using Polar RS800CX heart rate monitor and Flexi Force201 thin film type pressure sensor with MFF series pressure test system. Their subjective comfort evaluations were conducted by five-point Likert scale. Grey correlation analysis is used to determine the correlation degree of heart rate variation indexes and subjective comfort evaluations to identify the indexes preferably associated with subjective comfort. Multiple regression analysis is applied to investigate multiple correlations between pressure of test points and the indexes selected above.

Combined subjective comfort evaluation with objective HRV evaluation the heart rate variation indexes preferably associated with subjective comfort of these bras were identified, which includes mHR, mRR, RMSSD, pNN50. By the relationship between dynamic clothing pressure and the indexes above, this study finds that the clothing pressure of the chest area during basketball exercise should be controlled in the range of 2.01-4.74 kPa.

The subjects of different body type should be taken into account. Further, the mathematic models from this study show low R2-value so the models should be provided more reliable prediction.

The present study indicates that there is an inevitable connection between heart rate variation indexes and subjective comfort of basketball sports bras and creatively points out that heart rate variation indexes can partly assess the comfortable clothing pressure. The study can offer theoretical basis for sports apparel industry to develop the comfortable basketball sports bra.

The area shrinkage of the body under pressure is very important to evaluate the comfort of pressure sense, and it is an important index that appraises compression garment. The purpose of this paper is to obtain the area shrinkage mass of the waist cross section by using the finite-element method (FEM), and the waist of women’s pantyhose could be designed with a different degree of elasticity during the course of design based on clothing pressure comfort.

This study aimed at the problems existing in the wearing of women’s elastic pantyhose, took the waist of pantyhose as the research object, and the contact between human body and pantyhose as elastic contact. The finite-element model of the waist cross section and elastic pantyhose fabric was acquired through CT scan and Mimics software. After simulating on the corresponding displacement distribution of the waist of sample elastic pantyhose during the process of dressing by using ANSYS, the authors divided the waist cross section into 24 equal regions according to angle (every 15 degrees as a region), and then the area shrinkage mass of each region was obtained by area calculation formula. According to the tendency of area shrinkage distribution, the waist of women’s elastic pantyhose could be designed for different regions of tension considering the pressure comfort, so as to guarantee that the wearing comfort can be maintained on the premise of ensuring the functionality of the elastic pantyhose.

In this paper, the authors obtained the area shrinkage mass of elastic pantyhose at waist cross section, and this area shrinkage distribution could be used as an objective evaluation index for pressure comfort. All these solutions are of great significance to the optimization design of pantyhose and can provide theoretical basis for the structural improvement of functional pantyhose and the prediction of clothing pressure.

This paper simulated the area shrinkage mass for the waist of elastic pantyhose by using FEM, and the waist of women’s elastic pantyhose could be designed for different regions of tension considering the pressure comfort according to the area shrinkage distribution tendency, so as to guarantee the wearing comfort during the wearing process.

Objective appraisal of pressure comfort is the basement of optimal design of clothing. The purpose of this paper is to study a new method to appraise pressure comfort through displacement distribution, and then explored the multiple relationship between pressure and displacement on the lower leg cross-section using finite element method (FEM) and curve fitting.

This paper presented a 2D simulation model of the lower leg cross-section consisting of three layer different mechanical properties, namely skin, soft tissue, and bone. Analyzed the relationship and variation tendency between contact pressure and strain, calculated the multiple relationship between pressure and displacement on the lower leg cross-section where located at the top part of men’s socks in detail, and then obtained the quadratic functional equation between angle and pressure/displacement ratio through segmented curve fitting using Origin 7.5 software.

In this research work, the mathematical equation is obtained which describe the relationship between angle and pressure/displacement of the top part of men’s socks. On the premise of the known contact pressure values on the lower leg cross-section, the corresponding displacement values on the human body surface can be obtained by the functional equation under stress, and this displacement could be used as an objective evaluation index for pressure comfort. Based on these conclusions, the authors could provide theoretical reference for pressure prediction and optimizing the design of clothing.

This paper is unconcerned with the simulating of pressure, strain, and displacement distribution when dressing during the course of walking and running.

The paper analyzed the relationship and variation tendency between contact pressure and strain using FEM, and then obtained the quadratic functional equation between angle and pressure/displacement ratio of the top part of socks. It can supply a new method to appraise pressure comfort.

For comfort evaluation of underwear pressure, this paper proposes an improved GA algorithm to optimize the weight and threshold of BP neural network, namely PSO-GA-BP neural network prediction model.

The objective parameters of underwear, body shape data, skin deformation and other data are selected for simulation experiments to predict the objective pressure and subjective evaluation in dynamic and static state. Compared with the prediction results of BP neural network prediction model, GA-BP neural network prediction model and PSO-BP neural network prediction model, the performance of each prediction model is verified.

The results show that the BP neural network model optimized by PSO-GA algorithm can accelerate the convergence speed of the neural network and improve the prediction accuracy of underwear pressure.

PSO-GA-BP model provides data support for underwear design, production and processing and has guiding significance for consumers to choose underwear.

Since it has been regarded as an effective method to evaluate clothing pressure comfort with physiological and psychological techniques the purpose of this paper is to examine the effect on people s inhibition ability caused by the oppression from clothing on the body through event-related potentials (ERPs). A trial application of ERPs technology was made to evaluate clothing pressure comfort and investigate the relationship between some physical indexes of brain wave and clothing pressure. This research would also reveal the influence of clothing pressure on the thinking ability and mental activity of young women.

Stroop color-naming task was utilized to test the inhibition ability of participants. In the present research, some components of ERPs (e.g. N1, P2, N2 and N450) and behavioral indexes (RTs, and errors rates) were detected to verify the change of physiology and psychology caused by the pressure imposed by girdle on the body.

At behavioral level RTs were slower for the group under pressure rather than pressure-free group with no significant difference in errors rate between the two groups. Based on the early component statistics of ERPs the Stroop effects of both groups were similar. Besides there was no prominent difference in the latencies and amplitudes of N1, P2 and N2 components except the N450 components. The inhibition ability of young women who had worn girdle for 8 hours decreased causing them unable to make a timely response and thus affecting their attentiveness and executive ability.

This study would clarify that it is feasible to evaluate clothing pressure comfort with ERPs as a physiological technique, and enrich relative methods.

In order to study the wearing comfort of pressure for tight‐fit clothing, the sensation of wearing pressure and the other related sensations have been assessed for knit garments, which have different sizes and fabrics which have different extensibilities, by developing a wearing experimental procedure. Using factor analysis with principal factor solutions and rotated by the Varimax method, we obtained relevant factor matrices about the subjective assessment. At the same time, objective clothing pressure, fabric extensibility and garment fitness have been measured. Regression analysis showed that the garment fitness and fabric extensibility had great predictive power for the subjective pressure assessment.

In order to study the static and dynamic comfort of tight sportswear in winter, the subjective comfort was aimed to be evaluated by collecting sensory data such as humidity feeling, cold feeling and other perceptions. In this paper, the experiment was divided into standing, squatting, jumping, jogging, walking and so on.

Through particle swarm optimization-cuckoo search model, the sensory factors that affect the overall comfort were optimized, and it was found that there were great differences in the overall comfort factors under different motions. Then, analytic hierarchy process was used to sort the optimized sensory indicators in each experimental stage, and the influence degree of sensory indicators was studied. Finally, by the long short-term memory (LSTM) model, taking comfort senses of standing, squatting, jumping and jogging as input parameters, and regarding comfort senses of walking, lifting legs and resting as output parameters, the prediction model was founded.

The results showed that there were certain differences between the prediction value and the real subjective evaluation value, but most of the predicted values were consistent with the real values on the sensory level, and the overall prediction level was good, which meant that the LSTM model had more accurate prediction ability for subjective evaluation and could be extended to other sports.

The research results could provide scientific methods for the design of tight-fitting sportswear in winter.