Assistive Devices and Clothing: Exploring Adaptive Clothing Needs for Women with Lower Limb Prostheses Using the FEA Model

This study aimed to comprehensively investigate the essential considerations in designing adaptive clothing for women with lower limb prostheses in Saudi Arabia. Employing a qualitative methodology, the research entailed semi-structured, in-depth interviews with women utilizing lower limb prostheses and prosthetic specialists. This approach was selected to unearth pivotal design prerequisites and comprehend the specific challenges these women encounter within the realm of clothing. The utilization of selective sampling facilitated the collection of intricate and valuable insights. A Functional, Expressive, and Aesthetic (FEA) User Needs model was utilized to scrutinize participant feedback. Functional requisites encompass ease of dressing and undressing, accessibility to the prosthetic limb, comfort, mobility with the prosthesis, and appropriate fit. Additionally, participants highlighted various expressive needs, including privacy preservation, modesty, camouflaging disability appearances, maintaining alignment with non-disabled women’s fashion, and considerations about the aesthetic aspects of garments.

Enhancing Clothing Fit for Asian Women through Digital Transformation and Statistical Analysis

This study focuses on designing a solution to the perennial issue of clothing fit in Fashion Industry using tools offered by digital technology and statistical analysis, in particular, the data gathered on Asian women (Bangladeshi and Chinese). The study reveals that managing information can significantly enhance the capability of the industry to cater to the needs of its consumers and increase diversity. It centers on the effectiveness of turning dressmaking patterns into digital ones, thus transecting from traditional cutting and stitching to remote techniques. This entails the requirement to have correct self-measures and probable errors, which can arise in the process. Thus, with the help of regression analysis, the study identifies, which measurements are incorrect and influence the fit of the clothes, and, therefore, digital pattern creation is more accurate. Altogether, it can be observed how digitalization and statistical methods are crucial to transforming the way clothes are created to approach an ideal standard of measurements that fulfill every customer’s needs to make operational and efficient the clothing sector.

A Comparison of Cultures between China and the West——Taking Chinese Clothing and British Clothing as an Example

This paper attempts to do study on the comparison of differences between Chinese and western cultures by taking the Chinese and British clothing as an example. This comparison is made form two aspects about clothing culture. One is the separate characteristics of the Chinese and British clothing. The other is the common features of the Chinese and British clothing.The paper aims at making the Chinese confidently promote the clothing culture of China to make efforts to realize the great rejuvenation of China and enrich the culture of all mankind.

Computer Vision Evaluation of Clothing Fit

Most of the research on clothing fit is dependent on the subjective experience,and there are few studies involved in quantitative analysis.In this regard,this topic is innovative,it is the combination of image processing technology and garment fit evaluation.Through the background of the image noise reduction,edge extraction,reference point selection,to obtain the actual size.And according to the membership function to obtain the scope of the fit,the computer way to determine the degree of clothing fit.

Analysis and Research on the phenomenon of multifunction clothing

The changes of the times to update the mode of life, so that people in the material consumption at the same time. the more the pursuit of spiritual enjoyment of consumption.＂Multi function clothing＂ in a single product can transform a variety of clothing style,with multi - variability and fashion.Not only reduces the scale of production and people＇s pursuit of fashion personality contradiction between them, also make life and travel more lightweight, functional, and intelligent, increased interest and personality clothing experience. Its low energy consumption, high utilization and other advantages, but also the expression of the concept of low carbon environmental protection.Its characteristics conform to the development trend of the times and the concept of the times, it can also meet the diverse psychological demands of the consumers, and have great market potential.

Heat strain in chemical protective clothing in hot-humid environment:Effects of clothing thermal properties

Heat strain experienced by individuals wearing chemical protective clothing(CPC)is severe and dangerous especially in hot-humid environment.The development of material science and interdisciplinary studies including ergonomics,physiology and heat transfer is urgently required for the reduction of heat strain.The aim of this paper was to study the relationship among clothing thermal properties,physiological responses and environmental conditions.Three kinds of CPC were selected.Eight participants wore CPC and walked(4 km/h,two slopes with 5%and 10%)on a treadmill in an environment with(35±0.5)℃ and RH of(60±5)%.Core temperature,mean skin temperature,heart rate,heat storage and tolerance time were recorded and analyzed.Physiological responses were significantly affected by the clothing thermal properties and activity intensity in hot-humid environment.The obtained results can help further development of heat strain model.New materials with lower evaporative resistance and less weight are necessary to release the heat strain in hot-humid environments.

An Application of Grey Clustering Method in the Sporting Clothing Style Evaluation

In this paper, a Grey clustering method is applied to the evaluation research of sporting clothing style, the result shows that the methods proposed in the paper is feasible and effective.

Study on the Relation between the Air Gap Size under Clothing and the Comfort Sensations

Combining two non-contact testing instruments of a three-dimensional body measure system and an infrared camera, the entrapped air gap under clothing and the clothing surface temperature distribution were measured without interfering the air gap state. It was discussed the effect of different air gap size on subjective clothing sensation. At the same time, taken the subjective sensations of moisture, adhesiveness and mugginess from the lower back as example, the relationship among the subjective evaluation, the air gap size and the clothing surface temperature were analyzed.

Evaluation of Relationship Between Clothing Pressure of Men's Suit and Comfort

An investigation on relationship between clothing pressure of men's suit and wearing comfort is conducted. With the pressure measurements at different parts of men's suit under normal standing posture and in motion, the objective assessment of the total comfort are related to the subjective ratings of clothing pressure. There is a common strong sensation of pressure on shoulder with normal standing posture, and a strong relationship between total comfort and clothing pressure in back armhole and the front of upper arm with posture in motion.

Skin Sensitive Difference of Human Body Sections under Clothing— Smirnov Test of Skin Surface Temperatures' Dynamic Changing

Skin sensitive difference of human body sections under clothing is the theoretic foundation of thermal insulation clothing design. By a new method of researching on clothing comfort perception, the skin temperature live changing procedure of human body sections affected by the same cold stimulation is inspected. Furthermore with the Smirnov test the skin temperatures dynamic changing patterns of main human body sections are obtained.

Intelligence in Clothing Pattern CAD System

It analyzes three recognition methods for five elements,i.e.dot,line,loop,clothing pattern as well as characters,and also applies intelligent points and tangential curve in the CAD system to solve the problem complained by CAD users.It indicates that recognition of five elements is a foundational technique of intelligence in clothing pattern CAD system.Common functions in operation state such as move,rotation,flip,measure,should precede ones in element state as dot,line,and pattern.Moreover,it is realized that the less skill the CAD user needs,the more the CAD software is high-tech.

Analysis on the Application of Image Processing Technology in Clothing Pattern Recognition

A clothing pattern is a significant embodiment of regional culture and national characteristics.The recognition of clothing patterns could be realized objectively and accurately by using digital image processing technology.The researches on the extraction techniques of various pattern elements were compared and analyzed.Then the researches on clothing pattern color,outline and fabric texture extraction were summarized.And the core technology chain model of clothing pattern extraction was constructed.The research status,the core technology and the development trend of pattern element extraction technology based on two-dimensional images were obtained.What’s more,a reference for the follow-up research of clothing patterns and the technology upgrading of textile and clothing industries were provided.

Effects of Dressing Poses on Clothing Thermal Insulation

With a thermal manikin, the effects of dressing poses on clothing thermal insulation are studied. It is found that the thermal insulation of still air layer over human body has not been influenced by the dressing poses, but the dressing poses have effects on the thermal insulation of clothing system.

Feature Fusion Multi_XMNet Convolution Neural Network for Clothing Image Classification

Faced with the massive amount of online shopping clothing images,how to classify them quickly and accurately is a challenging task in image classification.In this paper,we propose a novel method,named Multi_XMNet,to solve the clothing images classification problem.The proposed method mainly consists of two convolution neural network(CNN)branches.One branch extracts multiscale features from the whole expressional image by Multi_X which is designed by improving the Xception network,while the other extracts attention mechanism features from the whole expressional image by MobileNetV3-small network.Both multiscale and attention mechanism features are aggregated before making classification.Additionally,in the training stage,global average pooling(GAP),convolutional layers,and softmax classifiers are used instead of the fully connected layer to classify the final features,which speed up model training and alleviate the problem of overfitting caused by too many parameters.Experimental comparisons are made in the public DeepFashion dataset.The experimental results show that the classification accuracy of this method is 95.38%,which is better than InceptionV3,Xception and InceptionV3_Xception by 5.58%,3.32%,and 2.22%,respectively.The proposed Multi_XMNet image classification model can help enterprises and researchers in the field of clothing e-commerce to automaticly,efficiently and accurately classify massive clothing images.

Narrow Pooling Clothing Classification Based on Attention Mechanism

In recent years,with the rapid development of e-commerce,people need to classify the wide variety and a large number of clothing images appearing on e-commerce platforms.In order to solve the problems of long time consumption and unsatisfactory classification accuracy arising from the classification of a large number of clothing images,researchers have begun to exploit deep learning techniques instead of traditional learning methods.The paper explores the use of convolutional neural networks(CNNs)for feature learning to enhance global feature information interactions by adding an improved hybrid attention mechanism(HAM)that fully utilizes feature weights in three dimensions:channel,height,and width.Moreover,the improved pooling layer not only captures local feature information,but also fuses global and local information to improve the misclassification problem that occurs between similar categories.Experiments on the Fashion-MNIST and DeepFashion datasets show that the proposed method significantly improves the accuracy of clothing classification(93.62%and 67.9%)compared with residual network(ResNet)and convolutional block attention module(CBAM).

Study of Adaptive Clothing in Hong Kong: Demands, Analysis and Future Direction

Aging population is substantively increased over last decade and they have specific clothing needs especially for the elderly with disabilities. Their clothing needs to cover functional and aesthetic requirements in order to improve their quality of life. Adaptive clothing is specially designed for the elderly and the disabled. However, there is no public policy to support such the elderly with disabilities in their clothing needs. In this paper, we aim to study the adaptive clothing and its significance, the problems encountered by the elderly with disabilities in adaptive clothing, analysis of public policy in Hong Kong for the elderly with disabilities in adaptive clothing over last decade, and implications and future directions for adaptive clothing in Hong Kong. In our findings, the demand of adaptive clothing in Hong Kong was substantially increased over last decade and the predicted demand will be twice of current demand after 50 years. However, the Government policy in Hong Kong has not yet fully supported their clothing needs, and the non-profit clothing services centre is set up to provide tailoring services to meet their needs. As the capacity of the centre is very limited, it is necessary to expand its capacity through assistive technology and to encourage non-government organizations (NGOs) to establish more social enterprises with Government’s support. Such findings would be beneficial to the Government for strengthening such services for the elderly and the disabled as well as public awareness.

Research on Clothing Simulation Design Based on Three-Dimensional Image Analysis

Traditional clothing design models based on adaptive meshes cannot reflect.To solve this problem,a clothing simulation design model based on 3D image analysis technology is established.The model uses feature extraction and description of image evaluation parameters,and establishes the mapping relationship between image features and simulation results by using the optimal parameter values,thereby obtaining a three-dimensional image simulation analysis environment.On the basis of this model,by obtaining the response results of clothing collision detection and the results of local adaptive processing of clothing meshes,the cutting form and actual cutting effect of clothing are determined to construct a design model.The simulation results show that compared with traditional clothing design models,clothing simulation design based on 3D image analysis technology has a better effect,with the definition of fabric folds increasing by 40%.More striking contrast between light and dark,the resolution increasing by 30%,and clothing details getting a more real manifestation.

Study on Protective Clothing against SARS Using PTFE/Poly(ether-ester) Membrane

By means of texturing with organic conductive fiber, and then being treated with JAM-Y1 anti-bacteria agent, in the end, treated with the XL-550 waterproof agent, the PET fabric has permanent antistatic, anti-bacteria and waterproof and anti-oil properties. The PET fabric was laminated with PTFE membrane by paste dot coating, and then coated by Poly(ether-ester) solution in a direct process. The filter efficiency of NaCl aerosol, penetration property of poliomyelitis virus in liquid and animalcule in air of PET fabric laminated with PTFE membrane are measured. The properties show that the PET fabric laminated with PTFE membrane can separate SARS virus in air and liquid. The protective mechanism is also discussed in the article.

Mathematical Simulation of Dynamic Heat Transfer in a Human-Clothing-Environment System

A mathematical model has been developed to describe the dynamic heat transfer in the clothing microclimate under transient wear conditions. This model is solved numerically by the implicit finite difference method. If the physical activity and ambient conditions are specified, the model can predict the thermoregulatory response of the body. Experimental measurements with garments made of fibers with different levels of hygroscopicity are compared with predictions by the model. There is good agreement between prediction and experiment for the temperature of the clothing microclimate.

Environmental Protection and Energy Color Changing Clothing Design under the Background of Sustainable Development

In order to promote the application of clean energy technology in clothing and promote the integration of industrial development and artificial intelligence wearable technology,this study elaborates the energy application characteristics of intelligent wearable products at home and abroad and its application in different fields,aiming at the current research status of wearable technology in the field of textile and clothing.The wearable distributed generation technology is classified,and a creative clothing design for detecting climate temperature is designed.Based on the monitoring of body temperature,the changes in clothing pattern color can reflect people’s health and emotional status.At the same time,it can also be applied to the screening of abnormal body temperature during the COVID-19.