{"url":"/dataset/eeg-and-p300-database-to-determine-the-signal","name":"EEG and P300 database to determine the signal to noise ratio during a variety of realistic tasks","full_name":null,"description_markdown":"This database contains EEG and evoked potential recordings from 20 participants. This allows to assess the signal to noise ratio:\r\n- Signal: The P300 power and VEP power can be used to assess the signal power\r\n- Noise: The signal power consisting of EMG and baseline EEG during the different tasks allows to determine the noise level","description_withheld":null,"homepage":"https://researchdata.gla.ac.uk/1258/","introduced_date":"2020-03-11","introduced_date_note":null,"introduced_by":{"paper":"/paper/a-real-time-noise-cancelling-eeg-electrode","title":"Real-time noise cancellation with Deep Learning","first_author":"Sama Daryanavard","url":null},"license":{"name":"Creative Commons Attribution 4.0 International License","url":"http://creativecommons.org/licenses/by/4.0/"},"modalities":[],"tasks":[],"languages":[],"variants":["EEG and P300 database to determine the signal to noise ratio during a variety of realistic tasks"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-25T09:33:49+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}