Titre :

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

Auteur(s) :

Cheng, Pengpeng [Auteur]
Génie des Matériaux Textiles - ULR 2461 [GEMTEX]
École nationale supérieure des arts et industries textiles [ENSAIT]
Wang, Jianping [Auteur]
Génie des Matériaux Textiles - ULR 2461 [GEMTEX]
École nationale supérieure des arts et industries textiles [ENSAIT]
Zeng, Xianyi [Auteur]
Génie des Matériaux Textiles - ULR 2461 [GEMTEX]
École nationale supérieure des arts et industries textiles [ENSAIT]
Bruniaux, Pascal [Auteur]
Génie des Matériaux Textiles - ULR 2461 [GEMTEX]
École nationale supérieure des arts et industries textiles [ENSAIT]
Chen, D. L. [Auteur]

Titre de la revue :

Fibres & Textiles in Eastern Europe

Nom court de la revue :

Fibres Text. East. Eur.

Numéro :

-

Pagination :

-

Date de publication :

2023-08-21

ISSN :

1230-3666

Mot(s)-clé(s) en anglais :

Motion state
Tight sportswear
Temperature and humidity
Prediction model

Discipline(s) HAL :

Sciences de l'ingénieur [physics]

Résumé en anglais : [en]

A neural network structure of Long Short Term Memory (LSTM) is proposed which could be used to predict the temperature and humidity of other key parts from the temperature and humidity data of some parts of the human body ...
Lire la suite >A neural network structure of Long Short Term Memory (LSTM) is proposed which could be used to predict the temperature 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 temperature 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. Keywords Motion state, Tight sportswear, Temperature and humidity, Prediction modelLire moins >

Langue :

Anglais

Audience :

Internationale

Vulgarisation :

Non

Établissement(s) :

Université de Lille
ENSAIT
Junia HEI

Collections :

• Génie des matériaux textiles (GEMTEX) - ULR 2641

Date de dépôt :

2024-05-06T21:13:03Z
2024-10-01T13:39:37Z