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EEG-Based BCIs on Motor Imagery Paradigm Using Wearable Technologies: A Systematic Review
Aurora Saibene1,2, Mirko Caglioni1, Silvia Corchs2,3
1Department of Informatics, Systems and Communication, University of Milano-Bicocca, Viale Sarca 336, 20126 Milano, Italy.
Sensors (Basel, Switzerland)
|March 11, 2023
Summary
This review examines wearable electroencephalographic (EEG) brain-computer interfaces (BCIs) using motor imagery (MI). It assesses technological and computational maturity, identifying benchmarks for future BCI development.
Area of Science:
- Neuroscience and Biomedical Engineering
- Human-Computer Interaction
Background:
- Electroencephalographic (EEG) technologies have driven significant growth in brain-computer interfaces (BCIs).
- Wearable neurotechnology advancements enable BCIs beyond clinical settings, expanding their application scope.
- Motor imagery (MI) presents a promising paradigm for EEG-based BCIs.
Approach:
- A systematic review adhering to PRISMA guidelines was conducted.
- Analysis focused on EEG-based BCIs utilizing wearable devices and the MI paradigm.
- 84 publications from 2012 to 2022 were critically evaluated.
Key Points:
- Evaluated the technological maturity of wearable EEG-BCI systems.
- Assessed the computational aspects and methodologies employed in these systems.
- Cataloged experimental paradigms and datasets to establish benchmarks.
Conclusions:
- Identified key areas for improvement in wearable EEG-BCI technology and computational models.
- Provided guidelines for the development of next-generation BCIs.
- Highlighted the potential of MI-based wearable BCIs for diverse applications.
