Fusing Stretchable Sensing Technology with Machine Learning for Human–Machine Interfaces

Ming Wang, Ting Wang, Yifei Luo, Ke He, Liang Pan, Zheng Li, Zequn Cui, Zhihua Liu, Jiaqi Tu, Xiaodong Chen*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

120 Citations (Scopus)

Abstract

Sensors and algorithms are two fundamental elements to construct intelligent systems. The recent progress in machine learning (ML) has produced great advancements in intelligent systems, owing to the powerful data analysis capability of ML algorithms. However, the performance of most systems is still hindered by sensing techniques that typically rely on rigid and bulky sensor devices, which cannot conform to irregularly curved and dynamic surfaces for high-quality data acquisition. Skin-like stretchable sensing technology with unique characteristics, such as high conformability, low modulus, and light weight, has been recently developed to solve this issue. Here, the recent progress in the fusion of emerging stretchable electronics and ML technology, for bioelectrical signal recognition, tactile perception, and multimodal integration is summarized, and the challenges and future developments are further discussed. These efforts aim to accelerate various perception and reasoning tasks for advanced intelligent applications, such as human–machine interfaces, healthcare, and robotics.

Original languageEnglish
Article number2008807
JournalAdvanced Functional Materials
Volume31
Issue number39
DOIs
Publication statusPublished - Sept 23 2021
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2021 Wiley-VCH GmbH

ASJC Scopus Subject Areas

  • Electronic, Optical and Magnetic Materials
  • General Chemistry
  • Biomaterials
  • General Materials Science
  • Condensed Matter Physics
  • Electrochemistry

Keywords

  • artificial intelligence
  • electronic skin
  • human–machine interfaces
  • machine learning
  • stretchable sensors

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