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In particular, EEG-based motor imagery (MI) BCI faces large variability and low signal-to-noise ratio. To address these issues, collecting a large and reliable dataset is critical for learning of cross-session and cross-subject patterns while mitigating EEG signals inherent instability. In this study, we obtained a comprehensive MI dataset from the 2019 World Robot Conference Contest-BCI Robot Contest. We collected EEG data from 62 healthy participants across three recording sessions. This experiment includes two paradigms: (1) two-class tasks: left and right hand-grasping, (2) three-class tasks: left and right hand-grasping, and foot-hooking. The dataset comprises raw data, and preprocessed data. For the two-class data, an average classification accuracy of 85.32% was achieved using EEGNet, while the three-class data achieved an accuracy of 76.90% using deepConvNet. Different researchers can reuse the dataset according to their needs. We hope that this dataset will significantly advance MI-BCI research, particularly in addressing cross-session and cross-subject challenges.<\/jats:p>","DOI":"10.1038\/s41597-025-04826-y","type":"journal-article","created":{"date-parts":[[2025,3,23]],"date-time":"2025-03-23T11:48:38Z","timestamp":1742730518000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["A multi-day and high-quality EEG dataset for motor imagery brain-computer interface"],"prefix":"10.1038","volume":"12","author":[{"given":"Banghua","family":"Yang","sequence":"first","affiliation":[]},{"given":"Fenqi","family":"Rong","sequence":"additional","affiliation":[]},{"given":"Yunlong","family":"Xie","sequence":"additional","affiliation":[]},{"given":"Du","family":"Li","sequence":"additional","affiliation":[]},{"given":"Jiayang","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Fu","family":"Li","sequence":"additional","affiliation":[]},{"given":"Guangming","family":"Shi","sequence":"additional","affiliation":[]},{"given":"Xiaorong","family":"Gao","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,3,23]]},"reference":[{"key":"4826_CR1","doi-asserted-by":"crossref","first-page":"041001","DOI":"10.1088\/1741-2552\/aba162","volume":"17","author":"R Mane","year":"2020","unstructured":"Mane, R., Chouhan, T. & Guan, C. 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