AMBER 2.0: A DATASET FOR NATURALISTIC SETTINGS WITH HMD-BASED RSVP TASKS

Building upon the foundation of AMBER (https://www.frontiersin.org/journals/neuroergonomics/articles/10.3389/fnrgo.2023.1216440/full), the AMBER 2.0 dataset was introduced to simulate more immersive real-world scenarios. The primary innovation in AMBER 2.0 is the use of a head-mounted display (HMD) for RSVP image presentation, replacing the traditional monitor setup. The full-length paper can be found here. AMBER 2.0 - Original Published Paper The AMBER 2.0 datasets provide comprehensive resources for advancing BCI research in naturalistic and real-world environments. By addressing the limitations of lab-constrained datasets, this dataset aims to facilitate the development of robust and reliable BCIs capable of handling the complexities of everyday use. AMBER 2.0 introduces immersive scenarios beyond the boundaries of a standard laboratory setting, through HMD-based RSVP tasks, marking significant strides toward practical BCI applications. The dataset serves as a benchmark for evaluating BCI algorithms and exploring the interplay of environmental factors, task demands, and user performance, paving the way for innovative applications in neurotechnology.