Smart Healthcare Clothing : An Analysis of Typology and Product Characteristics Using the FEA Framework

As the paradigm of healthcare shifts toward prevention and daily management due to an aging population, smart healthcare clothing has emerged as a promising solution for continuous health monitoring. However, despite technological advancements, mass adoption remains limited due to challenges regarding user comfort and aesthetic satisfaction. This study analyzes the characteristics of smart healthcare clothing using the FEA (Functional, Expressive, Aesthetic) model proposed by Lamb and Kallal (1992). Through a comprehensive review of literature and market cases, this study reveals that functional attributes, such as precise bio-signal sensing and washability, are fundamental prerequisites. However, expressive dimensions, which minimize the social stigma of patienthood through invisible technology or project a professional self-manager image, are crucial for user acceptance. Furthermore, aesthetic dimensions, including the use of premium materials and fashion-forward designs that harmonize with daily wear, are essential for bridging the gap between technology and apparel. The findings suggest that for smart healthcare clothing to transition from niche gadgets to sustainable everyday wear, development strategies must holistically integrate technical performance with the wearer’s emotional and aesthetic needs. This research provides a strategic framework for developing user-centric smart healthcare clothing that enhances both utility and satisfaction.

Authors

Publication Details

Journal
The Korean Society of Costume
Published
2026-02-28
DOI
https://doi.org/10.7233/jksc.2026.76.1.137
Primary Topic
Innovative Human-Technology Interaction
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Smart Healthcare Clothing : An Analysis of Typology and Product Characteristics Using the FEA Framework

Sunwoo Kim, Jihye Kim, Yuri Lee
The Korean Society of Costume
Innovative Human-Technology Interaction
article

Smart Healthcare Clothing : An Analysis of Typology and Product Characteristics Using the FEA Framework

Sunwoo Kim, Jihye Kim, Yuri Lee
article en

Abstract

As the paradigm of healthcare shifts toward prevention and daily management due to an aging population, smart healthcare clothing has emerged as a promising solution for continuous health monitoring. However, despite technological advancements, mass adoption remains limited due to challenges regarding user comfort and aesthetic satisfaction. This study analyzes the characteristics of smart healthcare clothing using the FEA (Functional, Expressive, Aesthetic) model proposed by Lamb and Kallal (1992). Through a comprehensive review of literature and market cases, this study reveals that functional attributes, such as precise bio-signal sensing and washability, are fundamental prerequisites. However, expressive dimensions, which minimize the social stigma of patienthood through invisible technology or project a professional self-manager image, are crucial for user acceptance. Furthermore, aesthetic dimensions, including the use of premium materials and fashion-forward designs that harmonize with daily wear, are essential for bridging the gap between technology and apparel. The findings suggest that for smart healthcare clothing to transition from niche gadgets to sustainable everyday wear, development strategies must holistically integrate technical performance with the wearer’s emotional and aesthetic needs. This research provides a strategic framework for developing user-centric smart healthcare clothing that enhances both utility and satisfaction.

The Korean Society of CostumeVol. 76(1)
Industry, innovation and infrastructure
Openalex Percentile: Top 29%
Innovative Human-Technology Interaction
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.