摘要：Global population aging poses an unprecedented challenge and calls for a rising efort in eldercare and healthcare. Steady-state visual evoked potential based brain-computer interface (SSVEP-BCI) boasts its high transfer rate and shows great promise in real-world applications to support aging. Public database is critically important for designing the SSVEP-BCI systems. However, the SSVEP- BCI database tailored for the elder is scarce in existing studies. therefore, in this study, we present a large eldercare-oriented BEnchmark database of SSVEP-BCI for the aging population (eldBEta). the eldBETA database consisted of the 64-channel electroencephalogram (EEG) from 100 elder participants, each of whom performed seven blocks of 9-target SSVEP-BCI task . The quality and characteristics of the eldBETA database were validated by a series of analyses followed by a classifcation analysis of thirteen frequency recognition methods . We expect that the eldBETA database would provide a substrate for the design and optimization of the BCI systems intended for the elders. the eldBEta database is open-access for research and can be downloaded from the website https://doi.org/10.6084/ m9.fgshare.18032669 .
