Challenges and Benefits to EEG-based Brain-Computer Interfaces in Neurorehabilitation

This systematic review presents and evaluates the current literature of the challenges and benefits associated with EEG-based brain computer interfaces (BCI) in neurorehabilitation. The research has focused on technical capabilities, clinical outcomes, and challenges of BCI found in the literature. The review was conducted using databases extracted from the University of North Georgia Library to include EBSCO, ProQuest, MedlinePlus, and PubMed. All literature searched in English that provided data related to the challenges and benefits in EEG-based BCI in the context of rehabilitation was included in the review from 2015 to present. In total, 13 papers met the inclusion criteria and were reviewed. We found that EEG-based BCIs demonstrate significant advantages in neurorehabilitation real-time feedback capabilities as an example of one benefit. We also found challenges in the BCI field as they target patients with difficulty generating EEG data compared to healthy controls. Since deep learning models incorporate several parameters, they require more data than conventional methods. A gap in literature has shown that additional research in BCI is needed. Even though there appear to be many challenges in EEG-based BCIs, the benefits far outweigh potential barriers created by or against the technology. However, as effective as the systematic literature review is in uncovering gaps in literature and research over the last decade, additional research will need to be conducted to uncover the benefits that outweigh the challenges.