Temperature and Humidity Data Evaluation of Tight Sportswear During Motion Based on Intelligent Modeling

• Autorzy: Cheng Pengpeng , Wang Jianping , Zeng Xianyi , Bruniaux Pascal , Chen Daoling

Identyfikatory

DOI

10.2478/ftee-2023-0021

• Języki publikacji: EN

Abstrakty

EN

A neural network structure of Long Short Term Memory (LSTM) is proposed which could be used to predict the temperaturę and humidity of other key parts from the temperature and humidity data of some parts of the human body when wearing tight sportswear, so as to realize the temperature and humidity data prediction of all key points of the human body. The temperaturę and humidity of different people wearing tights were collected by DHT sensors. The experimental results show that the LSTM neural network structure proposed has higher prediction accuracy than other algorithms, and the model evaluates the feasibility of temperature and humidity data of tights in a state of motion, which facilitates the study of dynamic thermal and humid comfort and reduces the time cost of analyzing the temperature and humidity distribution and changing the law during human movement. It will effectively promote the study of temperature and humidity changes when people wear sports tights, provide theoretical reference for the study of human skin temperature in the field of sports medicine, and provide practical guidance for the application of human skin temperature changes in sports clothing production, diagnosis and prevention of sports injuries.

Słowa kluczowe

EN

motion state; tight sportswear; temperature; humidity; prediction model

• Wydawca: Sieć Badawcza Łukasiewicz - Łódzki Instytut Technologiczny
• Czasopismo: Fibres & Textiles in Eastern Europe
• Rocznik: 2023
• Tom: Vol. 31, no. 3
• Strony: 1--8
• Opis fizyczny: Bibliogr. 24 poz., rys., tab.

Twórcy

autor

Cheng Pengpeng

• College of Fashion and Design, Donghua University, Shanghai, China
• Centrale Lille, Ensait, Gemtex, F-59000 Roubaix, France

autor

Wang Jianping

• College of Fashion and Design, Donghua University, Shanghai, China
• Key Laboratory of Clothing Design & Technology, Donghua University, Ministry of Education, Shanghai 200051, China
• Shanghai Belt and Road Joint Laboratory of Textile Intelligent Manufacturing, Shanghai 200051, China

autor

Zeng Xianyi

• Centrale Lille, Ensait, Gemtex, F-59000 Roubaix, France

autor

Bruniaux Pascal

• Centrale Lille, Ensait, Gemtex, F-59000 Roubaix, France

autor

Chen Daoling

• Clothing and Design Faculty, Minjiang University, Fuzhou, China

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