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Noninvasive Human-Prosthesis Interfaces for Locomotion Intent Recognition: A Review.
Dongfang Xu1,2, Qining Wang1,2,3
1Robotics Research Group, College of Engineering, Peking University, China.
Cyborg and Bionic Systems (Washington, D.C.)
|October 26, 2022
Summary
Recognizing user intent is crucial for lower-limb robotic prostheses. This review explores noninvasive sensing methods for locomotion intent recognition, offering a framework for improved prosthetic control.
Area of Science:
- Biomedical Engineering
- Robotics
- Human-Computer Interaction
Background:
- Lower-limb robotic prostheses aim to restore mobility for amputees.
- Accurate and timely user intent recognition is essential for effective prosthetic control.
- Current intent recognition methods face significant challenges in real-world applications.
Purpose of the Study:
- To review state-of-the-art noninvasive sensing techniques for lower-limb robotic prosthesis user intent recognition.
- To analyze different recognition tasks: locomotion mode, gait event detection, and gait phase estimation.
- To provide a comprehensive overview of current research, challenges, and future directions.
Main Methods:
- Systematic review of existing literature on intent recognition for lower-limb prostheses.
- Analysis of noninvasive sensing modalities and their application in intent recognition.
- Categorization of recognition approaches based on task (mode, event, phase).
Main Results:
- Identified key sensing methods and algorithms used in locomotion intent recognition.
- Highlighted the progress and limitations of current techniques across different recognition tasks.
- Discussed the critical role of various elements within the recognition approach.
Conclusions:
- Intent recognition is a complex but vital area for advanced prosthetic functionality.
- A generalized framework for intent recognition in lower-limb prostheses is proposed.
- Future research should focus on improving accuracy, robustness, and real-time performance.
