Intelligent Thermochromic Heating E‑Textile for Personalized Temperature Control in Healthcare

Heating electronic textiles (e-textiles) are widely used for thermal comfort and energy conservation, but prolonged heating raises concerns about heat-related illnesses, especially in the elderly. Despite advancements, achieving universal user satisfaction remains difficult due to diverse thermal ne...

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Published inACS applied materials & interfaces Vol. 17; no. 3; pp. 5515 - 5526
Main Authors Lee, Ching, Tan, Jeanne, Tan, Jun Jong, Tang, Hiu Ting, Yu, Wing Shan, Lam, Ngan Yi Kitty
Format Journal Article
LanguageEnglish
Published United States American Chemical Society 22.01.2025
Subjects
Artificial Intelligence
caregivers
color
consumer satisfaction
discoloration
elderly
energy conservation
fabrics
health services
heat
Heating - instrumentation
Hot Temperature
Humans
optical fibers
polymers
Surfaces, Interfaces, and Applications
Temperature
Textiles
Wearable Electronic Devices
wireless technology
heating textile
intelligent textile
thermochromic textile and healthcare
temperature control
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Summary:Heating electronic textiles (e-textiles) are widely used for thermal comfort and energy conservation, but prolonged heating raises concerns about heat-related illnesses, especially in the elderly. Despite advancements, achieving universal user satisfaction remains difficult due to diverse thermal needs. This paper introduces an intelligent thermochromic heating e-textile with an artificial intelligence (AI)-based temperature control system for optimized personal comfort and color indicators for elderly caregivers. The fabric integrates conductive yarn, temperature-induced discoloration yarn (TIDY), and polymeric optical fiber (POF) to visualize temperature changes, ensuring efficiency and comfort. Equipped with microcontrollers, ambient sensors, and Bluetooth connectivity, the system offers comprehensive intelligent heating solutions. An AI model, trained on data from 50 wearability test subjects, determines optimal heating temperatures (40–50 °C) with 5.083 mean squared error (MSE), showing a high correlation between predicted and actual comfort levels. This concept enhances thermal comfort and mitigates overheating risks, promising for wearable healthcare applications.
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ISSN:1944-8244
1944-8252
1944-8252
DOI:10.1021/acsami.4c19174