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EEG-Based BCIs on Motor Imagery Paradigm Using Wearable Technologies: A Systematic Review.

Aurora Saibene^1,2, Mirko Caglioni¹, Silvia Corchs^2,3

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.

Keywords:

brain–computer interface (BCI)electroencephalogram (EEG)motor imagery (MI)wearable devices

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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.