A Brain-Computer Interface Application Based on P300 Evoked EEG Potentials for Enabling the Communication Between Users and Chat GPT

The brain-computer interface or the BCI is a high-technology provided by the breakthroughs from the biomedical engineering research field. The BCI is aimed at supporting people with neuromotor disabilities by enabling the achievement of movement and communication tasks using only the mental decoded intentions. This paper presents the development and the experimentation of BCI application integrated with the Chat GPT assistant. Considering that this AI modern instrument is really engaging triggering the feeling of communicating with a real human being, then it will prove its usefulness even for the disabled users who need to be treated as normal persons still having unaffected emotions and cognitive abilities. The EEG signals are acquired from the GTEC Unicorn headset embedding eight sensors placed to the frontal, parietal, temporal, and occipital cerebral lobes. The current work also focuses on the implementation of a LabVIEW instrument providing the solution of calling specific Python functions able to achieve the data transfer between computer and the Chat GPT API. Therefore, the originality is determined by solving the challenge underlying the software development of a functional brain-computer interface by combining LabVIEW graphical programming environment, Python language and P300 Speller Unicorn platform. This way, the users firstly need to focus their attention and eyesight to the alphanumeric symbols displayed by the Speller board. The target is to obtain simultaneous real-time data transfer starting with the questions addressed by the P300 Speller board and ending with the answers provided by the Chat GPT.