Dataset of Easy Screen P300 Speller Brain–Computer Interface Design

A dataset has been created to support advancements in brain-computer interface (BCI) research, particularly focusing on P300 speller systems and electroencephalography (EEG) signal analysis. This dataset provides detailed EEG recordings from 30 healthy participants during offline analysis, online character recognition, and word-writing tasks. A 16-channel Brain Products V-Amp device was utilized, and data were collected via a 7×7 visual stimulus matrix designed to evoke reliable P300 responses, with stimuli presented in randomized sequences. The dataset comprises raw EEG signals, binary labels, and stimulus timing information, structured to facilitate the development of innovative BCI algorithms and real-time applications. This open-access resource enables novel approaches to EEG signal classification and supports the design of adaptive P300 speller interfaces, offering a foundation for advancing assistive technologies and neuroscience research.