A Comprehensive Review of the Movement Imaginary Brain-Computer Interface Methods: Challenges and Future Directions

A Comprehensive Review of the Movement Imaginary Brain-Computer Interface Methods: Challenges and Future Directions Publisher

Khademi S¹ ; Neghabi M¹ ; Farahi M² ; Shirzadi M³ ; Marateb HR^{1, 3}

Show Affiliations

1. Biomedical Engineering Department, Engineering Faculty, University of Isfahan, Isfahan, Iran
2. Department of Medical Physics and Biomedical Engineering, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
3. Biomedical Engineering Research Centre (CREB), Automatic Control Department (ESAII), Polytechnic University of Catalonia (UPC), Barcelona, Spain

Source: Artificial Intelligence-Based Brain-Computer Interface Published:2022

Abstract

Brain-computer interface (BCI) aims to translate human intention into a control output signal. In motor-imaginary (MI) BCI, the imagination of movement modifies the cortex brain activity. Such activities are then used in pattern recognition to identify certain movement classes. MI-BCI could be used to enhance the life quality of physically impaired subjects. Several challenges exist in MI-BCI, including selecting appropriate channels, usually linked with a suitable classifier choice. The entire procedure must be real time in practical applications. A variety of channel selection and classification methods were used for MI-BCI in the literature. Also, hybrid machine learning (ML) and deep learning (DL) methods were used in the literature. In this chapter, different channel selection, ML and DL methods, validation frameworks, and performance indices of EEG-based methods were investigated. Three hundred and twenty-two papers published between January 2000 and March 2021 were analyzed in this systematic review. Specific challenges and future directions were then provided. © 2022 Elsevier Inc. All rights reserved.

2. The 2017 and 2018 Iranian Brain-Computer Interface Competitions, Journal of Medical Signals and Sensors (2020)

Experts (# of related papers)

Bahador Makkiabadi (2)

Amir Homayoun Jafari (1)

Style	Citing Format
MLA	Khademi S, et al.. "A Comprehensive Review of the Movement Imaginary Brain-Computer Interface Methods: Challenges and Future Directions." Artificial Intelligence-Based Brain-Computer Interface, vol. , no. , 2022, pp. 23-74.
APA	Khademi S, Neghabi M, Farahi M, Shirzadi M, Marateb HR (2022). A Comprehensive Review of the Movement Imaginary Brain-Computer Interface Methods: Challenges and Future Directions. Artificial Intelligence-Based Brain-Computer Interface, (), 23-74.
Chicago	Khademi S, Neghabi M, Farahi M, Shirzadi M, Marateb HR. "A Comprehensive Review of the Movement Imaginary Brain-Computer Interface Methods: Challenges and Future Directions." Artificial Intelligence-Based Brain-Computer Interface , no. (2022): 23-74.
Harvard	Khademi S et al. (2022) 'A Comprehensive Review of the Movement Imaginary Brain-Computer Interface Methods: Challenges and Future Directions', Artificial Intelligence-Based Brain-Computer Interface, (), pp. 23-74.
Vancouver	Khademi S, Neghabi M, Farahi M, Shirzadi M, Marateb HR. A Comprehensive Review of the Movement Imaginary Brain-Computer Interface Methods: Challenges and Future Directions. Artificial Intelligence-Based Brain-Computer Interface. 2022;():23-74.
BibTex	@article{ author = {Khademi S and Neghabi M and Farahi M and Shirzadi M and Marateb HR}, title = {A Comprehensive Review of the Movement Imaginary Brain-Computer Interface Methods: Challenges and Future Directions}, journal = {Artificial Intelligence-Based Brain-Computer Interface}, volume = {}, number = {}, pages = {23-74}, year = {2022} }
RIS	TY - JOUR AU - Khademi S AU - Neghabi M AU - Farahi M AU - Shirzadi M AU - Marateb HR TI - A Comprehensive Review of the Movement Imaginary Brain-Computer Interface Methods: Challenges and Future Directions JO - Artificial Intelligence-Based Brain-Computer Interface VL - IS - SP - 23 EP - 74 PY - 2022 ER -

Science Communicator Platform

Authors

Authors Affiliations

Abstract