Enhancing Sensory Perception through Haptic Vests for Outside Field of View Attention Assistance Dataset

This dataset contains electroencephalographic (EEG) recordings from a subject engaged in a dual-task paradigm involving a primary Stroop task and a secondary collaborative activity with a cobot. Subjects had headphones streaming pink noise. In .set format, the dataset includes an associated STUDY file detailing dipole clustering from Independent Component Analysis (ICA) decomposition using the AMICA algorithm. The study investigates cognitive processing and task-switching dynamics, with task-switching prompted by haptic or visual cues.Tasks OverviewThe Stroop task requires the participant to identify the ink color of incongruent words, engaging cognitive control and selective attention. Concurrently, the secondary task involves motor responses during cobot collaboration, which simulates shared attentional demands. This setup replicates complex work environments, exploring how individuals allocate attention to manage simultaneous tasks and respond to sensory cues for task switching.EEG AnalysisEEG data were processed using ICA to isolate neural sources and map dipole locations. Clustering of dipoles identified brain regions involved in dual-task performance and differentiated neural patterns for each task-switch trigger (haptic vs. visual). The clustered dipole data offer insights into brain activity in response to sensory cue modalities when visual and auditory senses are saturated.