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Motor imagery across three recording sessions: two-class and three-class cohorts, kept apart

WBCIC-SHU motor imagery dataset: EEG decoding results

The WBCIC-SHU motor imagery dataset (Figshare+ 22671172) holds EEG from 62 healthy participants, each recorded in three sessions with the same motor-imagery paradigm: 51 in a two-class task (left- or right-hand grasping) and 11 in a three-class task that adds foot-hooking. It was collected at the 2019 World Robot Conference BCI robot contest with a 64-channel wireless Neuracle cap at 1,000 Hz, and the release holds raw data, a processed derivative and code. Released by Banghua Yang and Fenqi Rong (Shanghai University) and described in Scientific Data (2025). Only the processed derivative of sessions 1 and 3 is used here.

Also known as WBCIC-SHU · WBCIC-SHU Motor Imagery Dataset · WBCIC_SHU Motor Imagery dataset · Figshare+ 22671172 · A multi-day and high-quality EEG dataset for motor imagery brain-computer interface · Yang et al. (2025)

Description sources doi.org · doi.org · api.figshare.com

Where it appears

Published results

Every figure below is copied from a reviewed download, not recomputed for this page.

Later sessions · two-class motor imagery, session 1 to session 3

Read with its protocol: Later sessions · Chance level 50.0% · later-sessions-update.json

Relative spectral power + ridge
53.9% (52.7%–55.1%)
CBraMod · frozen encoder, session-1 ridge readout
67.7% (64.8%–70.5%)
Balanced accuracy, 2 configurations. Dot: the estimate; line: 95% interval; dashed line: chance level where the payload records one.
MethodConditionMetricValuePeople
Source-majority priorreference or comparator, not a decoding modelSession 1 → session 3 · no session-3 labelsBalanced accuracy50.0%One over the number of classes: a floor, not a model.51
Relative spectral power + ridgeSession 1 → session 3 · no session-3 labelsBalanced accuracy53.9%52.7%–55.1%51
Relative spectral power + ridgeMinus the source prior, the same people and trialsPaired difference+3.9 pp+2.7 pp–+5.1 pp51
CBraMod · frozen encoder, session-1 ridge readoutSession 1 → session 3 · no session-3 labelsBalanced accuracy67.7%64.8%–70.5%51
CBraMod · frozen encoder, session-1 ridge readoutMinus the relative spectral ridge, the same people and trialsPaired difference+13.8 pp+11.3 pp–+16.4 ppA comparison of two fixed pipelines on reused test trials; it does not show that pretraining caused the gain, and whether this checkpoint saw WBCIC-SHU in pretraining is not established.51

Later sessions · three-class motor imagery, session 1 to session 3

Read with its protocol: Later sessions · Chance level 33.3% · later-sessions-update.json

Relative spectral power + ridge
37.6% (35.4%–40.0%)
CBraMod · frozen encoder, session-1 ridge readout
51.6% (45.2%–58.3%)
Balanced accuracy, 2 configurations. Dot: the estimate; line: 95% interval; dashed line: chance level where the payload records one.
MethodConditionMetricValuePeople
Source-majority priorreference or comparator, not a decoding modelSession 1 → session 3 · no session-3 labelsBalanced accuracy33.3%One over the number of classes: a floor, not a model.11
Relative spectral power + ridgeSession 1 → session 3 · no session-3 labelsBalanced accuracy37.6%35.4%–40.0%11
Relative spectral power + ridgeMinus the source prior, the same people and trialsPaired difference+4.3 pp+2.1 pp–+6.6 pp11
CBraMod · frozen encoder, session-1 ridge readoutSession 1 → session 3 · no session-3 labelsBalanced accuracy51.6%45.2%–58.3%11
CBraMod · frozen encoder, session-1 ridge readoutMinus the relative spectral ridge, the same people and trialsPaired difference+14.0 pp+7.5 pp–+20.8 ppA comparison of two fixed pipelines on reused test trials; it does not show that pretraining caused the gain, and whether this checkpoint saw WBCIC-SHU in pretraining is not established.11

Source and licence

WBCIC-SHU motor imagery dataset

Credit Banghua Yang, Fenqi Rong, Yunlong Xie, Du Li, Jiayang Zhang, Fu Li, Guangming Shi and Xiaorong Gao · A multi-day and high-quality EEG dataset for motor imagery brain-computer interface, Scientific Data 12, 488 (2025), doi:10.1038/s41597-025-04826-y. Data: Banghua Yang and Fenqi Rong, WBCIC-SHU Motor Imagery Dataset, Figshare+, doi:10.25452/figshare.plus.22671172.v5, CC BY 4.0. Derived analysis by BCI Report; not endorsed by the authors.

CC BY 4.0 ↗ · Dataset record ↗

BCI Report does not redistribute any recording. These are aggregate measurements computed by BCI Report under the licence above; the data belong to the people credited.

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Cite this page

BCI Report (2026). WBCIC-SHU motor imagery dataset: EEG decoding results. https://bci.report/datasets/wbcic-shu/

Figures from release later-sessions-update-20261008 (2026-10-08). Cite the upstream dataset as well: its credit is on this page.

Every release is archived on Zenodo: doi:10.5281/zenodo.23123296. BibTeX for the site and its releases → · CITATION.cff ↗