An EEG Pattern Depicting the Attention of Customers While Viewing Video Advertisements

Attention is a complex cognitive process of the brain that is crucial for our everyday functioning. The electroencephalogram (EEG) may be utilised to measure and assess attention due to its high temporal resolution. Despite the existence of several suggested attention recognition braincomputer interfaces (BCIs), there has been a shortage of research including a substantial number of participants, suitable paradigms, and consistent analysis of recognition across people. This study examines the impact of visual stimulus quality on electroencephalogram (EEG) signals and cognitive engagement. Visual cues are essential for triggering brain responses and cognitive processes. This research conducted an experiment to investigate the attention and non-attention states of participants during data gathering, both when they were stimulated and when they were not (baseline). The Mean Absolute Value (MAV) and Standard Deviation (STD) were used to assess the attention degree of participant’s EEG signals in relation to varying visual stimuli. The results of our study demonstrate a notable reduction in brain activity in the occipital areas when individuals are paying high attention, as opposed to low attention. In addition, it was shown that both MAV and STD features consistently dropped during active visual engagement, in comparison to baseline circumstances without stimuli. The MAV and STD are reduced by an average of $\mathbf{2 2 \%}$ during low attention compared to the baseline, while during high attention, both features decreased by $\mathbf{5 3 \%}$. The results might be ascribed to a phenomenon known as event-related desynchronization (ERD), which denotes the reduction in amplitude of EEG signals in particular frequency ranges during high attention or focus.