Skip to main navigation Skip to search Skip to main content

Wearable technologies for assisted mobility in the real world

  • Shuo Gao*
  • , Jianan Chen
  • , Yunjia Xia
  • , Xuemeng Li
  • , Weihao Ma
  • , Huixin Yang
  • , Jinchen Li
  • , Xinkai Zhou
  • , Tianyu Jia
  • , Yuchen Xu
  • , Julie Uchitel
  • , Dean Ta
  • , Peng Qi
  • , Junbo Ge
  • , Yi Guo
  • , Yajie Qin
  • , Inseung Kang
  • , Wenyao Xu
  • , He Li
  • , Jinke Chang
  • Siming Zuo, Shiwei Wang, Shan Luo, Letizia Gionfrida, Chen Hu, Shuqin Dong, Yongxin Guo, Yixuan Yuan, Haixia Zhang, Haotian Chen, Yu Pan, Chenyun Dai, Qinyuan Ren, Rui Loureiro, Tom Carlson, Wei Chen, Yuanting Zhang, Panicos Kyriacou, Hadi Heidari, Kia Nazarpour, Themis Prodromakis, Alexander Casson, Tamar R. Makin, Gert Cauwenberghs*, Dario Farina*, Hubin Zhao*
*Corresponding author for this work
  • University College London
  • Beihang University
  • Imperial College London
  • University of California at San Diego
  • Stanford University
  • Fudan University
  • Tongji University
  • Carnegie Mellon University
  • SUNY Buffalo
  • Southeast University, Nanjing
  • University of Oxford
  • University of Glasgow
  • University of Edinburgh
  • King's College London
  • City University of Hong Kong
  • National University of Singapore
  • Chinese University of Hong Kong
  • Peking University
  • Tsinghua University
  • Shanghai Jiao Tong University
  • Zhejiang University
  • The University of Sydney
  • City St George's, University of London
  • University of Manchester
  • MRC Cognition and Brain Sciences Unit

Research output: Contribution to journalReview articlepeer-review

Abstract

Mobility impairments from aging, injury, or medical conditions limit independence and social participation. Conventional assistive devices lack adaptability in complex environments. Recent wearable technologies integrating neural sensing, electronics, and co-design offer personalized, responsive mobility support. This perspective focuses on advances in wearable sensing and multimodal fusion for intent recognition, environmental interaction, and adaptive control in exoskeletons, prosthetics, smart wheelchairs, and navigation systems. Emphasizing human-in-the-loop and cognitive–sensorimotor integration, it outlines emerging trends and challenges, promoting intelligent, user-centered solutions to restore function and enhance autonomy, accessibility, and inclusion for individuals with mobility impairments.

Original languageEnglish
Article number10988
JournalNature Communications
Volume16
Issue number1
DOIs
StatePublished - Dec 2025

Fingerprint

Dive into the research topics of 'Wearable technologies for assisted mobility in the real world'. Together they form a unique fingerprint.

Cite this