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Control strategies for trunk exoskeletons based on motion intent recognition: A review
Ruyu Yuan1, Qingqing Wang1, Haipeng Xu2
1Institute of Rehabilitation Engineering and Technology, University of Shanghai for Science and Technology, Shanghai, China.
Neurorehabilitation
|June 29, 2024
Summary
Intention recognition control is key for wearable trunk exoskeletons. This review analyzes control schemes for intelligent trunk exoskeletons, focusing on body movement signals for assistance and augmentation.
Area of Science:
- Robotics
- Human-Computer Interaction
- Biomedical Engineering
Background:
- Wearable trunk exoskeletons offer significant potential in healthcare and industry.
- Intention recognition control is vital for effective user interaction with exoskeletons.
Purpose of the Study:
- To review intention recognition control schemes for intelligent trunk exoskeletons.
- To analyze control characteristics based on different objectives over the past decade.
Main Methods:
- Systematic literature review of papers from 2013-2023.
- Searches conducted on Web of Science, PubMed, and IEEE Xplore databases.
- Analysis of 50 selected articles based on four control objectives.
Main Results:
- Focus on trunk exoskeleton devices for assistance and motor augmentation.
- Body movement signals are predominantly used for intention recognition.
- Research trends indicate a growing emphasis on user-centric control.
Conclusions:
- Identified promising research directions for widely accepted control methods.
- Recommendations for advancing trunk exoskeleton technology development.
- Future work should explore more sophisticated intention recognition algorithms.
