Emerging Technologies for Assistive Robotics: Current Challenges and Future Perspectives

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Artificial Intelligence".

Deadline for manuscript submissions: 15 August 2025 | Viewed by 414

Special Issue Editors

Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518005, China
Interests: lower limb exoskeletons; intelligent prosthesis; rehabilitation robotics; human–machine interaction
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Guest Editor
Institute of Intelligent Rehabilitation Engineering of USST, University of Shanghai for Science and Technology, Shanghai 200093, China
Interests: soft exoskeletons; rehabilitation robotics; intelligent prosthesis
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Guest Editor
School of Automation, Beijing University of Posts and Telecommunications, Beijing 100876, China
Interests: medical rehabilitation robot; elderly care robot; home service robot; allosteric unmanned system

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Guest Editor
Sino-German College of Intelligent Manufacturing, Shenzhen Technology University, Shenzhen 518118, China
Interests: wheelchair mobile robot; automatic cruise and handling robot; wearable exoskeleton robot; brain-computer interface; humanoid robot

Special Issue Information

Dear Colleagues,

We are excited to announce a new Special Issue entitled "Emerging Technologies for Assistive Robotics: Current Challenges and Future Perspectives". This Special Issue aims to gather innovative research regarding the rapid evolution of assistive robotics, a field that could transform the lives of individuals with disabilities or special needs.

We welcome submissions from researchers, engineers, and practitioners across various disciplines, including robotics, artificial intelligence, biotechnology, and healthcare. We are particularly interested in articles that explore the latest technological advancements in assistive robotics, such as exoskeletons, wearable devices, and autonomous assistants, as well as their potential applications in daily living, rehabilitation, and elderly care.

In addition to showcasing groundbreaking research, we encourage contributors to critically analyze the current challenges faced by the field, including technical limitations, ethical considerations, and societal barriers. We also welcome discussions concerning innovative solutions that could overcome these challenges and promote the development of more inclusive and accessible robotics.

Dr. Wujing Cao
Prof. Dr. Qiaoling Meng
Prof. Dr. Jian Li
Prof. Dr. Chi Zhu
Guest Editors

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Keywords

  • assistive robotics
  • wearable sensing systems
  • rehabilitation robotics
  • exoskeleton robots
  • intelligent prosthesis
  • human–robot interaction

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Published Papers (1 paper)

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Research

16 pages, 8051 KiB  
Article
Design and Joint Dynamics of Human Recumbent Rehabilitation Training Devices
by Qiulong Wu, Chaoyue Sun, Yi Liu, Sikai Wang, Jian Li and Peng Su
Electronics 2025, 14(9), 1724; https://doi.org/10.3390/electronics14091724 - 23 Apr 2025
Viewed by 166
Abstract
(1) Background: Patients bedridden due to accidental injuries, diseases, or age-related functional impairments require accelerated recovery of autonomous limb movement. A prone-position rehabilitation training device was developed to provide training intensity tailored to patients’ motor capabilities. (2) Methods: Based on principles of human [...] Read more.
(1) Background: Patients bedridden due to accidental injuries, diseases, or age-related functional impairments require accelerated recovery of autonomous limb movement. A prone-position rehabilitation training device was developed to provide training intensity tailored to patients’ motor capabilities. (2) Methods: Based on principles of human prone limb motion mechanics and torque balance, this study analyzed joint torque during limb movements using optical motion capture and six-dimensional force plate data. Joint torque curves during prone-position training were simulated, and a prototype device was developed. Prototype assembly and experimental validation of device–human synergy was conducted. (3) Results: Comparative analysis of joint torques between healthy individuals and patients revealed that joint torque increases as limbs contract inward. The maximum torque for upper limb joints was approximately 3.5 Nm, while the knee joint torque reached around 40 Nm. (4) Conclusions: Prototype testing confirmed the device’s design rationality, meeting human–machine synergy and rehabilitation training intensity requirements. This study provides a reference for the design of prone-position rehabilitation training devices. Full article
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