eldBETA: A Large Eldercare-oriented Benchmark Database of SSVEP-BCI for the Aging Population

Global population aging poses an unprecedented challenge and calls for a rising effort 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 <strong>eld</strong>ercare-oriented <strong>BE</strong>nchmark database of SSVEP-BCI for <strong>T</strong>he <strong>A</strong>ging population (eldBETA). The eldBETA database consisted of the 64-channel electroencephalogram (EEG) from 100 elder subjects, each of whom performed seven blocks of 9-target SSVEP-BCI task. We expect that the eldBETA database would provide a substrate for the design and optimization of the BCI systems intended for the elders.