A Comprehensive Analysis of the Design of Brain-Computer Interface Systems Utilizing Electroencephalography as a Means of Measurement: A Survey

With the use of Brain-Computer Interface (BCI) technologies, the brain and the outside world can communicate directly, bypassing the peripheral nervous system. This concept is fascinating as it acknowledges that the cells in our brain are electrical signals generated by neurons, which are the brain's information-processing units. The techniques for processing these electrical signals are crucial for mapping this electrical activity to develop reliable brain-computer interfaces. Electroencephalography (EEG) stands out as one of the most commonly utilized Brain-Computer Interface (BCI) techniques, primarily due to its ease of use and non-invasive characteristics. The capacity of a BCI system to interpret patterns of cognitive activity through computational algorithms to manipulate external devices is a key aspect of this technology. In the present study, an examination is conducted on the potential for researchers engaged in the analysis of EEG signals originating from the brain, encompassing methodologies reliant on multi-channel EEG data as well as diverse physiological signals. The focus extends to applications developed since 2018 and subsequent years, delving into details such as the nature of the data employed, specifications of the equipment utilized for capturing electrical signals for control purposes, the number of electrodes deployed, the volume of participants involved in data generation essential for cutting-edge BCI applications, techniques for obtaining EEG features and the optimal accuracy achievement levels in the said applications. Overall, BCI technology is a promising field with a vast range of applications. As technology advances, we can expect to see more sophisticated and reliable brain-computer interfaces that can be applied to enhance the lives of those who are disabled and neurological disorders.