{"url":"/dataset/motor-imagery-dataset-from-weibo-et-al-2014","name":"Motor Imagery dataset from Weibo et al 2014.","full_name":"MI Weibo et al 2014.","description_markdown":"Dataset from the article *Evaluation of EEG oscillatory patterns and\r\n    cognitive process during simple and compound limb motor imagery* [1]_.\r\n\r\nIt contains data recorded on 10 subjects, with 60 electrodes.\r\n\r\nThis dataset was used to investigate the differences of the EEG patterns\r\nbetween simple limb motor imagery and compound limb motor\r\nimagery. Seven kinds of mental tasks have been designed, involving three\r\ntasks of simple limb motor imagery (left hand, right hand, feet), three\r\ntasks of compound limb motor imagery combining hand with hand/foot\r\n(both hands, left hand combined with right foot, right hand combined with\r\nleft foot) and rest state.\r\n\r\nAt the beginning of each trial (8 seconds), a white circle appeared at the\r\ncenter of the monitor. After 2 seconds, a red circle (preparation cue)\r\nappeared for 1 second to remind the subjects of paying attention to the\r\ncharacter indication next. Then red circle disappeared and character\r\nindication (‘Left Hand’, ‘Left Hand & Right Foot’, et al) was presented on\r\nthe screen for 4 seconds, during which the participants were asked to\r\nperform kinesthetic motor imagery rather than a visual type of imagery\r\nwhile avoiding any muscle movement. After 7 seconds, ‘Rest’ was presented\r\nfor 1 second before next trial (Fig. 1(a)). The experiments were divided\r\ninto 9 sections, involving 8 sections consisting of 60 trials each for six\r\nkinds of MI tasks (10 trials for each MI task in one section) and one\r\nsection consisting of 80 trials for rest state. The sequence of six MI\r\ntasks was randomized. Intersection break was about 5 to 10 minutes.\r\n\r\nReferences\r\n-----------\r\n[1] Yi, Weibo, et al. \"Evaluation of EEG oscillatory patterns and\r\n       cognitive process during simple and compound limb motor imagery.\"\r\n       PloS one 9.12 (2014). https://doi.org/10.1371/journal.pone.0114853","description_withheld":null,"homepage":"https://dataverse.harvard.edu/api/access/datafile/2499178","introduced_date":null,"introduced_date_note":null,"introduced_by":null,"license":null,"modalities":[{"name":"EEG","url":"/datasets/modality/eeg"}],"tasks":[{"name":"Motor Imagery Decoding (left-hand vs right-hand)","url":"/task/motor-imagery-decoding-left-hand-vs-right","datasets_with_task":"/datasets/task/motor-imagery-decoding-left-hand-vs-right"}],"languages":[],"variants":["Motor Imagery dataset from Weibo et al 2014."],"data_loaders":[],"num_papers_in_archive":0,"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."}