Intelligent Soft Wearables
Name
3714394.3750561.pdf
Size
3.31 MB
Format
Adobe PDF
Checksum (MD5)
db44ffc6f163018d3e507a8927827787
Author(s)
Yu, Tianhong
Honnet, Cedric
Cheng, Tingyu
Takahashi, Ryo
Zhou, Bo
Zhang, Cheng
Lukowicz, Paul
Kawahara, Yoshihiro
Hester, Josiah
Paradiso, Joseph
Date Issued
December 29, 2025
Publisher
ACM|Companion of the 2025 ACM International Joint Conference on Pervasive and Ubiquitous Computing
Citation
Tianhong Catherine Yu, Cedric Honnet, Tingyu Cheng, Ryo Takahashi, Bo Zhou, Cheng Zhang, Paul Lukowicz, Yoshihiro Kawahara, Josiah Hester, Joseph A. Paradiso, Yiyue Luo, and Irmandy Wicaksono. 2026. Intelligent Soft Wearables. In Companion of the 2025 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp Companion '25). Association for Computing Machinery, New York, NY, USA, 1123–1126.
Version
Final published version
Abstract
Human bodies are almost always in contact with soft materials like clothing, for warmth, protection, self-expression, etc. Recent advancements in intelligent soft wearables have augmented these on-body soft objects with computational functions and intelligence with little compromise on the softness and comforts of wearables, allowing prolonged wear. These innovations, which combine advanced soft sensor design, fabrication, and computational power, offer unprecedented opportunities to improve our health, productivity, and overall well-being with monitoring and assistive capabilities. However, the inherent physical properties of soft materials present unique challenges in achieving practical interactions. The complexity of intelligent soft wearables, multiplexing intricate designs, soft materials, flexible electronics, advanced signal processing algorithms, and machine learning models, necessitates collaborative efforts from experts across diverse domains. This workshop aims to bring together interested researchers and practitioners across relevant domains to discuss the challenges and opportunities of intelligent soft wearables.
MIT Department
Massachusetts Institute of Technology. Media Laboratory
Terms of Use
Creative Commons Attribution
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1145/3714394.3750561
