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Texoskeletons: developing the fundamental technologies for creating intelligent soft robotic clothing with integrated 1D sensors and actuators

  • Amy Lukomiak
  • , Rameesh Bulathsinghala
  • , Jack Varga
  • , Shuxin Meng
  • , Kalana Marasinghe
  • , Imaad Refai
  • , Biyon Fernando
  • , Amitkumar Patel
  • , Chamika M. Halloluwa-Arachchige
  • , Carlos Oliveira
  • , Arash M. Shahidi
  • , Zahra Rahemtulla
  • , Alexander Turner
  • , Ziyun Ding
  • , Bernard X.W. Liew
  • , Andy Kerr
  • , Ezio Preatoni
  • , Theo Hughes-Riley
  • , R. D.Ishara G. Dharmasena
  • , Pasindu Lugoda
  • Nottingham Trent University
  • Loughborough University
  • University of Nottingham
  • University of Birmingham
  • University of Essex
  • University of Strathclyde

Research output: Contribution to journalArticlepeer-review

2   Link opens in a new tab Citations (SciVal)

Abstract

Traditional wearable exoskeletons rely on rigid structures, which limit comfort, flexibility, and everyday usability. This work introduces the fundamental technologies to create the first soft, lightweight, intelligent textile-based exoskeletons (Texoskeletons) built using 1D sensors and actuators. This new approach ensures that the textiles maintain most of its conformability and allows the devices to be positioned anywhere on the body. Two different structural architectures of pneumatic 1D actuators are evaluated: single-material and two-material actuators. The two-material actuators display intrinsic bending behavior and perform better when positioned within knitted textiles, while single-material actuators deliver superior lifting performance. When three of these actuators are grouped within the textile, they lift loads exceeding 300 g. Additionally, the Texoskeleton comprises of novel 1D triboelectric sensors to capture user movements. After training a machine learning algorithm, the 1D triboelectric sensors classify wrist flexion–extension, ulnar–radial deviation, supination, and pronation with an accuracy of 85.71%. A wrist-worn prototype Texoskeleton sleeve incorporating 14 actuators and 4 sensors is created to demonstrate the device's lightweight and wearability. This technology has the potential to revolutionize personalized rehabilitation, immersive training, and human–machine interaction, paving the way for intelligent everyday clothing that adapts to user movements and needs in real-time.

Original languageEnglish
Article numbere75714
Number of pages15
JournalAdvanced Functional Materials
Volume36
Issue number60
Early online date6 May 2026
DOIs
Publication statusPublished - 27 Jul 2026

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Acknowledgements

The authors would like to sincerely thank Natalia Dantas for the invaluable contribution as a technical knitwear specialist and the assistance with the knitted samples. The authors would like to thank Iain Mitchell for designing and building the mould used in this project, and Richard Arm for the valuable support during the initial mould design phase.

Funding

This work was financially supported by an EPSRC Rehab Technology Network (EP/W000679/1) workshop grant. The work was also supported by the Royal Academy of Engineering under the Research Fellowship scheme (RF\202021\20\252), Royal Society NSFC International Exchanges Cost Share grant (IEC\NSFC\223116), and Loughborough University Vice Chancellor’s Research Cluster “SuS-Tex”.

FundersFunder number
Loughborough University
Royal Academy Of Engineering
EPSRC Rehab Technology NetworkEP/W000679/1
Royal Society NSFCIEC∖NSFC∖223116

Keywords

  • electronic textiles
  • exoskeletons
  • smart textiles
  • soft robotics
  • textile sensors
  • triboelectric sensors
  • wearable robotics

ASJC Scopus subject areas

  • General Chemistry
  • General Materials Science
  • Condensed Matter Physics

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