Digital electronics in fibres enable fabric-based machine-learning inference
Name
s41467-021-23628-5.pdf
Description
Published version
Size
4.72 MB
Format
Adobe PDF
Checksum (MD5)
17f24159b33a2e3c05606d6e6174a478
Author(s)
Loke, Gabriel
Khudiyev, Tural
Wang, Brian
Fu, Stephanie
Payra, Syamantak
Shaoul, Yorai
Fung, Johnny
Chatziveroglou, Ioannis
Chou, Pin-Wen
Chinn, Itamar
Date Issued
2021
Journal
Nature Communications
Publisher
Springer Science and Business Media LLC
Citation
Loke, Gabriel, Khudiyev, Tural, Wang, Brian, Fu, Stephanie, Payra, Syamantak et al. 2021. "Digital electronics in fibres enable fabric-based machine-learning inference." Nature Communications, 12 (1).
Version
Final published version
Abstract
AbstractDigital devices are the essential building blocks of any modern electronic system. Fibres containing digital devices could enable fabrics with digital system capabilities for applications in physiological monitoring, human-computer interfaces, and on-body machine-learning. Here, a scalable preform-to-fibre approach is used to produce tens of metres of flexible fibre containing hundreds of interspersed, digital temperature sensors and memory devices with a memory density of ~7.6 × 105 bits per metre. The entire ensemble of devices are individually addressable and independently operated through a single connection at the fibre edge, overcoming the perennial single-fibre single-device limitation and increasing system reliability. The digital fibre, when incorporated within a shirt, collects and stores body temperature data over multiple days, and enables real-time inference of wearer activity with an accuracy of 96% through a trained neural network with 1650 neuronal connections stored within the fibre. The ability to realise digital devices within a fibre strand which can not only measure and store physiological parameters, but also harbour the neural networks required to infer sensory data, presents intriguing opportunities for worn fabrics that sense, memorise, learn, and infer situational context.
MIT Department
Massachusetts Institute of Technology. Department of Materials Science and Engineering
Massachusetts Institute of Technology. Research Laboratory of Electronics
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology. Department of Mechanical Engineering
Massachusetts Institute of Technology. Institute for Soldier Nanotechnologies
Massachusetts Institute of Technology. Department of Physics
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Creative Commons Attribution 4.0 International license
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DOI of Published Version
https://doi.org/10.1038/S41467-021-23628-5
