Thermo-Physiological Comfort Properties of Sportswear with Different Combination of Inner and Outer Layers

Atalie, Desalegn; Těšinová, Pavla; Tadesse, Melkie Getnet; Ferede, Eyasu; Dulgheriu, Ionuț; Loghin, Emil

doi:10.3390/ma14226863

Cited by 22 publications

(16 citation statements)

References 39 publications

(47 reference statements)

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“…I cl estimation relying on lookup tables in ISO standards [8][9][10]12] and updated clothes databases [58,59] can be a fast solution for laboratory studies, but it is unfeasible to use such a scheme in real applications due to reasons: (i) looking up the I cl value for a person needs extra manual work which is tedious and expensive; (ii) if this look-up task is expected to be done automatically, the solution must have the ability to recognize hundreds of different garment combinations that vary in materials and number of layers as the latest research has revealed the significant importance of them in thermal comfort [2], which is far beyond the capability of existing algorithms.…”

Section: CL Estimationmentioning

confidence: 99%

“…This kind of method takes advantage of different thermal properties (thermal resistance, thermal conductivity, thermal radiation, thermal convection, water evaporation, etc.) of different clothes in materials, thicknesses, and layers to maintain the body temperature in a comfortable range [2][3][4][5]. The other kind of method still focuses on the entire indoor environment but in a way that adjusts the microclimate according to each occupant's thermal need, which is the topic of this paper.…”

Section: Introductionmentioning

confidence: 99%

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Clothing Insulation Rate and Metabolic Rate Estimation for Individual Thermal Comfort Assessment in Real Life

Liu

Foged

Moeslund

2022

Sensors

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Satisfactory indoor thermal environments can improve working efficiencies of office staff. To build such satisfactory indoor microclimates, individual thermal comfort assessment is important, for which personal clothing insulation rate (Icl) and metabolic rate (M) need to be estimated dynamically. Therefore, this paper proposes a vision-based method. Specifically, a human tracking-by-detection framework is implemented to acquire each person’s clothing status (short-sleeved, long-sleeved), key posture (sitting, standing), and bounding box information simultaneously. The clothing status together with a key body points detector locate the person’s skin region and clothes region, allowing the measurement of skin temperature (Ts) and clothes temperature (Tc), and realizing the calculation of Icl from Ts and Tc. The key posture and the bounding box change across time can category the person’s activity intensity into a corresponding level, from which the M value is estimated. Moreover, we have collected a multi-person thermal dataset to evaluate the method. The tracking-by-detection framework achieves a mAP50 (Mean Average Precision) rate of 89.1% and a MOTA (Multiple Object Tracking Accuracy) rate of 99.5%. The Icl estimation module gets an accuracy of 96.2% in locating skin and clothes. The M estimation module obtains a classification rate of 95.6% in categorizing activity level. All of these prove the usefulness of the proposed method in a multi-person scenario of real-life applications.

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Section: CL Estimationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Clothing Insulation Rate and Metabolic Rate Estimation for Individual Thermal Comfort Assessment in Real Life

Liu

Foged

Moeslund

2022

Sensors

View full text Add to dashboard Cite

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“…For example, textiles utilising fibre-based artificial muscles may react to sweating through contraction, thus exposing a larger skin area for improved cooling [6]. Combining different types of fabrics can also significantly affect the overall performance of clothing, allowing for clothes especially suited for a particular activity or climate [7]. Using modern technology, smart garments can also be designed to target very specific needs, such as treatment of physical disorders [8].…”

Section: State-of-the-artmentioning

confidence: 99%

A Thermal Model for Processing Data from Undergarment Sensors in Automatic Control of Actively Heated Clothing

et al. 2021

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Despite its recent growth in popularity, actively heated clothing still lacks the ability to cope with demanding user scenarios. As many of these deficiencies stem from an absence of automatic control, the authors propose a novel approach using a set of sensors embedded in the clothing to provide data about thermal comfort. Available sensors suffer from a lack of accuracy, as for practical reasons, they cannot be attached to the skin, whose temperature is usually used as a comfort indicator. To determine the magnitude of the problem, the authors conducted experiments, and a thermal model was proposed based on experimental findings; the output from the model was compared with the experimental reference data for three different upper body undergarments. The overall accuracy was found to be good: in most cases, the difference between the computed and reference skin temperatures did not exceed 0.5 °C. Furthermore, the model does not rely on unrealistic assumptions regarding the availability of parameters or measurement data. Our findings demonstrate that it is possible to create a thermal model that, when used for input data processing, allows undergarment temperature to be converted to skin temperature, allowing for automatic control of heating insets.

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“…The use of different material arrangements in sleeping bags has increased in recent years, allowing them to be used in a variety of conditions while maintaining comfort. The use of the most modern textile science and technology in the production of this type of materials is developing every day [ 12 , 13 , 14 ]. Winter sleeping bags must provide adequate thermal insulation, as well as protection against weather conditions, while summer sleeping bags must—oppositely—provide lower thermal insulation; therefore, different composition of raw materials should be considered.…”

Section: Introductionmentioning

confidence: 99%

“…Many previous studies focused on the study of thermal properties in single and double-layer structures with variable raw material compositions to achieve the optimal level of comfort [ 12 , 15 , 16 , 17 , 18 , 19 , 20 ].…”

Section: Introductionmentioning

confidence: 99%

Study of Influence of Atmospheric Conditions on the Thermal Properties of Sleeping Bags

2022

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The thermal properties of clothing products are influenced by external environmental parameters, such as temperature, humidity, air flow and parameters related to the user’s body, which mainly include temperature and humidity. Depending on the type of raw material, its thickness and the material manufacturing technique, clothing products are characterised by certain insulating properties to protect the human body from external factors. A multilayer system made of different material groups can change the thermal insulating capacity significantly, which cannot be determined by the testing of individual layers used in the production. In order to determine the influence of weather conditions on thermal insulation and air permeability, tests were carried out for two types of sleeping bags (summer and autumn) produced by the same manufacturer, differing in insulation thickness. Simulations were carried out using SolidWorks and verified using a Newton thermal mannequin. During tests, both the temperature (range from −20 °C to 20 °C) and humidity values were changed (range 40–80% humidity). For sleeping bags, the effective thermal insulation decreases along with the increase of temperature and decrease of humidity. It can be observed, for the autumn sleeping bags, that for a temperature of 20 °C and humidity of 60%, the thermal insulation is 1.063 m2·K·W−1, while for a temperature of −20 °C and humidity of 60% thermal insulation increases significantly and amounts to 1.111 m2·K·W−1. A similar situation occurs for the effective thermal insulation of a summer sleeping bag (20 °C/60% thermal insulation is 0.794 m2·K·W−1, while for −20 °C/60%—0.851 m2·K·W−1. During the tests, the humidity and temperature between the layers of the clothing system were also controlled, in order to learn more about the influence of these parameters on the thermal insulation properties of the sleeping bags.

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Thermo-Physiological Comfort Properties of Sportswear with Different Combination of Inner and Outer Layers

Cited by 22 publications

References 39 publications

Clothing Insulation Rate and Metabolic Rate Estimation for Individual Thermal Comfort Assessment in Real Life

Clothing Insulation Rate and Metabolic Rate Estimation for Individual Thermal Comfort Assessment in Real Life

A Thermal Model for Processing Data from Undergarment Sensors in Automatic Control of Actively Heated Clothing

Study of Influence of Atmospheric Conditions on the Thermal Properties of Sleeping Bags

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