{"url":"/dataset/motor-imagey-dataset-from-shin-et-al-2017","name":"Motor Imagey Dataset from Shin et al 2017","full_name":"Motor Imagery (Dataset A)","description_markdown":"## Data Acquisition\r\n\r\nEEG and NIRS data was collected in an ordinary bright room. EEG data was\r\nrecorded by a multichannel BrainAmp EEG amplifier with thirty active\r\nelectrodes (Brain Products GmbH, Gilching, Germany) with linked mastoids\r\nreference at 1000 Hz sampling rate. The EEG amplifier was also used to\r\nmeasure the electrooculogram (EOG), electrocardiogram (ECG) and respiration\r\nwith a piezo based breathing belt. Thirty EEG electrodes were placed on a\r\ncustom-made stretchy fabric cap (EASYCAP GmbH, Herrsching am Ammersee,\r\nGermany) and placed according to the international 10-5 system (AFp1, AFp2,\r\nAFF1h, AFF2h, AFF5h, AFF6h, F3, F4, F7, F8, FCC3h, FCC4h, FCC5h, FCC6h, T7,\r\nT8, Cz, CCP3h, CCP4h, CCP5h, CCP6h, Pz, P3, P4, P7, P8, PPO1h, PPO2h, POO1,\r\nPOO2 and Fz for ground electrode).\r\n\r\nNIRS data was collected by NIRScout (NIRx GmbH, Berlin, Germany) at 12.5 Hz\r\nsampling rate. Each adjacent source-detector pair creates one physiological\r\nNIRS channel. Fourteen sources and sixteen detectors resulting in\r\nthirty-six\r\nphysiological channels were placed at frontal (nine channels around Fp1,\r\nFp2, and Fpz), motor (twelve channels around C3 and C4, respectively) and\r\nvisual areas (three channels around Oz). The inter-optode distance was 30\r\nmm. NIRS optodes were fixed on the same cap as the EEG electrodes. Ambient\r\nlights were sufficiently blocked by a firm contact between NIRS optodes and\r\nscalp and use of an opaque cap.\r\n\r\nEOG was recorded using two vertical (above and below left eye) and two\r\nhorizontal (outer canthus of each eye) electrodes. ECG was recorded based\r\non\r\nEinthoven triangle derivations I and II, and respiration was measured using\r\na respiration belt on the lower chest. EOG, ECG and respiration were\r\nsampled\r\nat the same sampling rate of the EEG. ECG and respiration data were not\r\nanalyzed in this study, but are provided along with the other signals.\r\n\r\n## Experimental Procedure\r\n\r\nThe subjects sat on a comfortable armchair in front of a 50-inch white\r\nscreen. The distance between their heads and the screen was 1.6 m. They\r\nwere\r\nasked not to move any part of the body during the data recording. The\r\nexperiment consisted of three sessions of left and right hand MI (dataset\r\nA)and MA and baseline tasks (taking a rest without any thought) (dataset B)\r\neach. Each session comprised a 1 min pre-experiment resting period, 20\r\nrepetitions of the given task and a 1 min post-experiment resting\r\nperiod. The task started with 2 s of a visual introduction of the task,\r\nfollowed by 10 s of a task period and resting period which was given\r\nrandomly from 15 to 17 s. At the beginning and end of the task period, a\r\nshort beep (250 ms) was played. All instructions were displayed on the\r\nwhite\r\nscreen by a video projector. MI and MA tasks were performed in separate\r\nsessions but in alternating order (i.e., sessions 1, 3 and 5 for MI\r\n(dataset\r\nA) and sessions 2, 4 and 6 for MA (dataset B)). Fig. 2 shows the schematic\r\ndiagram of the experimental paradigm. Five sorts of motion artifacts\r\ninduced\r\nby eye and head movements (dataset C) were measured. The motion artifacts\r\nwere recorded after all MI and MA task recordings. The experiment did not\r\ninclude the pre- and post-experiment resting state periods.\r\n\r\n## Motor Imagery (Dataset A)\r\n\r\nFor motor imagery, subjects were instructed to perform haptic motor imagery\r\n(i.e. to imagine the feeling of opening and closing their hands as they\r\nwere\r\ngrabbing a ball) to ensure that actual motor imagery, not visual imagery,\r\nwas performed. All subjects were naive to the MI experiment. For the visual\r\ninstruction, a black arrow pointing to either the left or right side\r\nappeared at the center of the screen for 2 s. The arrow disappeared with a\r\nshort beep sound and then a black fixation cross was displayed during the\r\ntask period. The subjects were asked to imagine hand gripping (opening and\r\nclosing their hands) in a 1 Hz pace. This pace was shown to and repeated by\r\nthe subjects by performing real hand gripping before the experiment. Motor\r\nimagery was performed continuously over the task period. The task period\r\nwas finished with a short beep sound and a 'STOP' displayed for 1s on the\r\nscreen. The fixation cross was displayed again during the rest period and\r\nthe subjects were asked to gaze at it to minimize their eye movements. This\r\nprocess was repeated twenty times in a single session (ten trials per\r\ncondition in a single session; thirty trials in the whole sessions). In a\r\nsingle session, motor imagery tasks were performed on the basis of ten\r\nsubsequent blocks randomly consisting of one of two conditions: Either\r\nfirst left and then right hand motor imagery or vice versa.\r\n\r\n## References\r\n\r\n\r\n[1] Shin, J., von Lühmann, A., Blankertz, B., Kim, D.W., Jeong, J.,\r\nHwang, H.J. and Müller, K.R., 2017. Open access dataset for EEG+NIRS\r\nsingle-trial classification. IEEE Transactions on Neural Systems\r\nand Rehabilitation Engineering, 25(10), pp.1735-1745.\r\n\r\n[2] GNU General Public License, Version 3\r\n`<https://www.gnu.org/licenses/gpl-3.0.txt>`_","description_withheld":null,"homepage":"https://doi.org/10.1002/hbm.23730","introduced_date":null,"introduced_date_note":null,"introduced_by":null,"license":{"name":"GNU General Public License","url":"https://www.gnu.org/licenses/gpl-3.0.txt"},"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 Imagey Dataset from Shin et al 2017"],"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."}