<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>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.</p>
</abstract>

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.

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

Fibres & Textiles in Eastern Europe

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

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 Evaluation of Tight Sportswear during Motion Based on Intelligent Modeling

Article Category: Research Article

Pubblicato online: 01 set 2023

Pagine: 1 - 8

DOI: https://doi.org/10.2478/ftee-2023-0021

Parole chiave
Motion state, Tight sportswear, Temperature and humidity, Prediction model

© 2023 Łukasiewicz Research Network-Łódź Institute of Technology, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

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

Article Category: Research Article

Pubblicato online: 01 set 2023

Pagine: 1 - 8

DOI: https://doi.org/10.2478/ftee-2023-0021

Parole chiaveMotion state, Tight sportswear, Temperature and humidity, Prediction model

© 2023 Łukasiewicz Research Network-Łódź Institute of Technology, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Parole chiave
Motion state, Tight sportswear, Temperature and humidity, Prediction model