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One approach to therapy and training for the restoration of damaged muscles and motor systems is rehabilitation. EEG-assisted Brain-Computer Interface (BCI) may aid in restoring or enhancing the brain&#x2019;s lost motor abilities. Assisted by brain activity, BCI offers simple-to-use technology aids and robotic prosthetics. This systematic literature review (SLR) aims to explore the latest developments in BCI and motor control for rehabilitation. Additionally, typical EEG apparatuses available for BCI-driven rehabilitative purposes have been explored. Furthermore, a comparison of significant studies in rehabilitation assessment using machine learning techniques has been summarized. The results of this study may influence policymakers&#x2019; decisions regarding the use of EEG equipment, particularly wireless devices, to implement BCI technology. Moreover, the SLR results offer suggestions for further study. To identify the additional characteristics of each EEG equipment and determine which one is most suited for each industry, we plan on measuring the user experience based on various devices in future research.

A Survey of EEG and Machine Learning based methods for Neural Rehabilitation