{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T15:05:43Z","timestamp":1777734343662,"version":"3.51.4"},"reference-count":90,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,11,7]],"date-time":"2025-11-07T00:00:00Z","timestamp":1762473600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2025,11,7]],"date-time":"2025-11-07T00:00:00Z","timestamp":1762473600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"name":"College of Engineering Research Mini Grant Program and Dr. Jihye Bae's Start Up Funds provided by Department of Electrical and Computer Engineering at the University of Kentucky"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Sci Data"],"DOI":"10.1038\/s41597-025-06039-9","type":"journal-article","created":{"date-parts":[[2025,11,7]],"date-time":"2025-11-07T10:53:59Z","timestamp":1762512839000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["A large electroencephalogram database of freewill reaching and grasping tasks for brain machine interfaces"],"prefix":"10.1038","volume":"12","author":[{"given":"Bhoj Raj","family":"Thapa","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"John","family":"Boggess","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jihye","family":"Bae","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,11,7]]},"reference":[{"key":"6039_CR1","doi-asserted-by":"publisher","first-page":"407","DOI":"10.1016\/j.nec.2021.03.012","volume":"32","author":"I Cajigas","year":"2021","unstructured":"Cajigas, I. & Vedantam, A. Brain-Computer Interface, Neuromodulation, and Neurorehabilitation Strategies for Spinal Cord Injury. Neurosurgery Clinics of North America 32, 407\u2013417, https:\/\/doi.org\/10.1016\/j.nec.2021.03.012 (2021).","journal-title":"Neurosurgery Clinics of North America"},{"key":"6039_CR2","doi-asserted-by":"publisher","first-page":"245","DOI":"10.1177\/155005941104200410","volume":"42","author":"S Silvoni","year":"2011","unstructured":"Silvoni, S. et al. Brain-Computer Interface in Stroke: A Review of Progress. Clinical EEG and Neuroscience 42, 245\u2013252, https:\/\/doi.org\/10.1177\/155005941104200410 (2011).","journal-title":"Clinical EEG and Neuroscience"},{"key":"6039_CR3","doi-asserted-by":"publisher","unstructured":"Vaughan, T. M. Brain-computer interfaces for people with amyotrophic lateral sclerosis. Handbook of Clinical Neurology 33\u201338, https:\/\/doi.org\/10.1016\/b978-0-444-63934-9.00004-4 (2020).","DOI":"10.1016\/b978-0-444-63934-9.00004-4"},{"key":"6039_CR4","doi-asserted-by":"publisher","unstructured":"Waldert, S. Invasive vs. Non-Invasive Neuronal Signals for Brain-Machine Interfaces: Will One Prevail? Frontiers in Neuroscience 10, https:\/\/doi.org\/10.3389\/fnins.2016.00295 (2016).","DOI":"10.3389\/fnins.2016.00295"},{"key":"6039_CR5","doi-asserted-by":"publisher","first-page":"140","DOI":"10.1109\/RBME.2011.2172408","volume":"4","author":"G Schalk","year":"2011","unstructured":"Schalk, G. & Leuthardt, E. C. Brain-Computer Interfaces Using Electrocorticographic Signals. IEEE Reviews in Biomedical Engineering 4, 140\u2013154, https:\/\/doi.org\/10.1109\/RBME.2011.2172408 (2011).","journal-title":"IEEE Reviews in Biomedical Engineering"},{"key":"6039_CR6","doi-asserted-by":"publisher","first-page":"383","DOI":"10.1146\/annurev-bioeng-071910-124640","volume":"15","author":"ML Homer","year":"2013","unstructured":"Homer, M. L., Nurmikko, A. V., Donoghue, J. P. & Hochberg, L. R. Sensors and Decoding for Intracortical Brain Computer Interfaces. Annual Review of Biomedical Engineering 15, 383\u2013405, https:\/\/doi.org\/10.1146\/annurev-bioeng-071910-124640 (2013).","journal-title":"Annual Review of Biomedical Engineering"},{"key":"6039_CR7","doi-asserted-by":"publisher","unstructured":"Naseer, N. & Hong, K.-S. fNIRS-based brain-computer interfaces: a review. Frontiers in Human Neuroscience 9, https:\/\/doi.org\/10.3389\/fnhum.2015.00172 (2015).","DOI":"10.3389\/fnhum.2015.00172"},{"key":"6039_CR8","doi-asserted-by":"publisher","unstructured":"Sorger, B. & Goebel, R. Real-time fMRI for brain-computer interfacing. Handbook of Clinical Neurology 289\u2013302, https:\/\/doi.org\/10.1016\/b978-0-444-63934-9.00021-4 (2020).","DOI":"10.1016\/b978-0-444-63934-9.00021-4"},{"key":"6039_CR9","doi-asserted-by":"publisher","first-page":"E108","DOI":"10.1093\/neuros\/nyz286","volume":"86","author":"ML Martini","year":"2019","unstructured":"Martini, M. L. et al. Sensor Modalities for Brain-Computer Interface Technology: A Comprehensive Literature Review. Neurosurgery 86, E108\u2013E117, https:\/\/doi.org\/10.1093\/neuros\/nyz286 (2019).","journal-title":"Neurosurgery"},{"key":"6039_CR10","doi-asserted-by":"publisher","first-page":"552","DOI":"10.1016\/j.tibtech.2010.08.002","volume":"28","author":"B-K Min","year":"2010","unstructured":"Min, B.-K., Marzelli, M. J. & Yoo, S.-S. Neuroimaging-based approaches in the brain\u2013computer interface. Trends in biotechnology 28, 552\u2013560, https:\/\/doi.org\/10.1016\/j.tibtech.2010.08.002 (2010).","journal-title":"Trends in biotechnology"},{"key":"6039_CR11","doi-asserted-by":"publisher","unstructured":"Portillo-Lara, R., Tahirbegi, B., Chapman, C. A. R., Goding, J. A. & Green, R. A. Mind the gap: State-of-the-art technologies and applications for EEG-based brain\u2013computer interfaces. APL Bioengineering 5, https:\/\/doi.org\/10.1063\/5.0047237 (2021).","DOI":"10.1063\/5.0047237"},{"key":"6039_CR12","doi-asserted-by":"publisher","unstructured":"Rashid, M. et al. Current Status, Challenges, and Possible Solutions of EEG-Based Brain-Computer Interface: A Comprehensive Review. Frontiers in Neurorobotics 14, https:\/\/doi.org\/10.3389\/fnbot.2020.00025 (2020).","DOI":"10.3389\/fnbot.2020.00025"},{"key":"6039_CR13","doi-asserted-by":"publisher","unstructured":"Lazarou, I., Nikolopoulos, S., Petrantonakis, P. C., Ioannis Kompatsiaris & Tsolaki, M. EEG-Based Brain\u2013Computer Interfaces for Communication and Rehabilitation of People with Motor Impairment: A Novel Approach of the 21st Century. Frontiers in Human Neuroscience 12, https:\/\/doi.org\/10.3389\/fnhum.2018.00014 (2018).","DOI":"10.3389\/fnhum.2018.00014"},{"key":"6039_CR14","doi-asserted-by":"publisher","unstructured":"Cao, L. et al. A Synchronous Motor Imagery Based Neural Physiological Paradigm for Brain Computer Interface Speller. Frontiers in Human Neuroscience 11, https:\/\/doi.org\/10.3389\/fnhum.2017.00274 (2017).","DOI":"10.3389\/fnhum.2017.00274"},{"key":"6039_CR15","doi-asserted-by":"publisher","unstructured":"Pan, J. et al. Advances in P300 brain\u2013computer interface spellers: toward paradigm design and performance evaluation. Frontiers in Human Neuroscience 16, https:\/\/doi.org\/10.3389\/fnhum.2022.1077717 (2022).","DOI":"10.3389\/fnhum.2022.1077717"},{"key":"6039_CR16","doi-asserted-by":"publisher","first-page":"3156","DOI":"10.1109\/tbme.2013.2270283","volume":"60","author":"NY Li","year":"2013","unstructured":"Li, N. Y., Pan, N. J., Wang, N. F. & Yu, N. Z. A Hybrid BCI System Combining P300 and SSVEP and Its Application to Wheelchair Control. IEEE Transactions on Biomedical Engineering 60, 3156\u20133166, https:\/\/doi.org\/10.1109\/tbme.2013.2270283 (2013).","journal-title":"IEEE Transactions on Biomedical Engineering"},{"key":"6039_CR17","doi-asserted-by":"publisher","first-page":"147","DOI":"10.1016\/j.procs.2016.04.080","volume":"84","author":"R Roy","year":"2016","unstructured":"Roy, R., Mahadevappa, M. & Kumar, C. S. Trajectory Path Planning of EEG Controlled Robotic Arm Using GA. Procedia Computer Science 84, 147\u2013151, https:\/\/doi.org\/10.1016\/j.procs.2016.04.080 (2016).","journal-title":"Procedia Computer Science"},{"issue":"2","key":"6039_CR18","doi-asserted-by":"publisher","first-page":"229","DOI":"10.1007\/s13246-015-0345-6","volume":"38","author":"M Serdar Bascil","year":"2015","unstructured":"Serdar Bascil, M., Tesneli, A. Y. & Temurtas, F. Multi-channel EEG signal feature extraction and pattern recognition on horizontal mental imagination task of 1-D cursor movement for brain computer interface. Australasian physical & engineering sciences in medicine 38(2), 229\u2013239, https:\/\/doi.org\/10.1007\/s13246-015-0345-6 (2015).","journal-title":"Australasian physical & engineering sciences in medicine"},{"key":"6039_CR19","doi-asserted-by":"publisher","first-page":"132","DOI":"10.1109\/tbme.2011.2167718","volume":"59","author":"NJ Long","year":"2011","unstructured":"Long, N. J., Li, N. Y., Yu, N. T. & Gu, N. Z. Target Selection With Hybrid Feature for BCI-Based 2-D Cursor Control. IEEE Transactions on Biomedical Engineering 59, 132\u2013140, https:\/\/doi.org\/10.1109\/tbme.2011.2167718 (2011).","journal-title":"IEEE Transactions on Biomedical Engineering"},{"key":"6039_CR20","doi-asserted-by":"publisher","first-page":"104","DOI":"10.1109\/tbme.2017.2694818","volume":"65","author":"M Nakanishi","year":"2017","unstructured":"Nakanishi, M. et al. Enhancing Detection of SSVEPs for a High-Speed Brain Speller Using Task-Related Component Analysis. IEEE Transactions on Biomedical Engineering 65, 104\u2013112, https:\/\/doi.org\/10.1109\/tbme.2017.2694818 (2017).","journal-title":"IEEE Transactions on Biomedical Engineering"},{"key":"6039_CR21","doi-asserted-by":"publisher","first-page":"33","DOI":"10.1016\/j.jneumeth.2014.03.011","volume":"229","author":"L Cao","year":"2014","unstructured":"Cao, L., Li, J., Ji, H. & Jiang, C. A hybrid brain computer interface system based on the neurophysiological protocol and brain-actuated switch for wheelchair control. Journal of Neuroscience Methods 229, 33\u201343, https:\/\/doi.org\/10.1016\/j.jneumeth.2014.03.011 (2014).","journal-title":"Journal of Neuroscience Methods"},{"key":"6039_CR22","doi-asserted-by":"publisher","first-page":"129","DOI":"10.1016\/j.irbm.2018.02.001","volume":"39","author":"R Bousseta","year":"2018","unstructured":"Bousseta, R., El Ouakouak, I., Gharbi, M. & Regragui, F. EEG Based Brain Computer Interface for Controlling a Robot Arm Movement Through Thought. IRBM 39, 129\u2013135, https:\/\/doi.org\/10.1016\/j.irbm.2018.02.001 (2018).","journal-title":"IRBM"},{"key":"6039_CR23","doi-asserted-by":"publisher","first-page":"824","DOI":"10.1002\/hbm.21248","volume":"33","author":"M Lu","year":"2011","unstructured":"Lu, M., Arai, N., Tsai, C. & Ziemann, U. Movement related cortical potentials of cued versus self-initiated movements: Double dissociated modulation by dorsal premotor cortex versus supplementary motor area rTMS. Human Brain Mapping 33, 824\u2013839, https:\/\/doi.org\/10.1002\/hbm.21248 (2011).","journal-title":"Human Brain Mapping"},{"key":"6039_CR24","doi-asserted-by":"publisher","unstructured":"Savic, A. M., Niazi, I. K. & Popovic, M. B. Self-paced vs. cue-based motor task: The difference in cortical activity. Research Portal Denmark 39\u201342, https:\/\/doi.org\/10.1109\/TELFOR.2011.6143887 (2011).","DOI":"10.1109\/TELFOR.2011.6143887"},{"key":"6039_CR25","doi-asserted-by":"publisher","first-page":"98","DOI":"10.1007\/s00221-002-1220-8","volume":"147","author":"S Jankelowitz","year":"2002","unstructured":"Jankelowitz, S. & Colebatch, J. Movement-related potentials associated with self-paced, cued and imagined arm movements. Experimental Brain Research 147, 98\u2013107, https:\/\/doi.org\/10.1007\/s00221-002-1220-8 (2002).","journal-title":"Experimental Brain Research"},{"key":"6039_CR26","doi-asserted-by":"publisher","unstructured":"Kaya, M., Mustafa Kemal Binli, Ozbay, E., Hilmi Yanar & Yuriy Mishchenko. A large electroencephalographic motor imagery dataset for electroencephalographic brain computer interfaces. Scientific Data 5, https:\/\/doi.org\/10.1038\/sdata.2018.211 (2018).","DOI":"10.1038\/sdata.2018.211"},{"key":"6039_CR27","doi-asserted-by":"publisher","first-page":"539","DOI":"10.1016\/j.neuroimage.2007.01.051","volume":"37","author":"B Blankertz","year":"2007","unstructured":"Blankertz, B., Dornhege, G., Krauledat, M., M\u00fcller, K.-R. & Curio, G. The non-invasive Berlin Brain\u2013Computer Interface: Fast acquisition of effective performance in untrained subjects. NeuroImage 37, 539\u2013550, https:\/\/doi.org\/10.1016\/j.neuroimage.2007.01.051 (2007).","journal-title":"NeuroImage"},{"key":"6039_CR28","unstructured":"Brunner, C., Leeb, R., M\u00fcller-Putz, G., Schl\u00f6gl, A. & Pfurtscheller, G. BCI Competition 2008 -Graz data set A Experimental paradigm. https:\/\/lampx.tugraz.at\/\u223cbci\/database\/001-2014\/description.pdf."},{"key":"6039_CR29","unstructured":"Leeb, R., Brunner, C., M\u00fcller-Putz, G., Schl\u00f6gl, A. & Pfurtscheller, G. BCI Competition 2008 -Graz data set B Experimental paradigm. https:\/\/www.bbci.de\/competition\/iv\/desc_2b.pdf."},{"key":"6039_CR30","doi-asserted-by":"publisher","unstructured":"Meng, J. et al. Noninvasive Electroencephalogram Based Control of a Robotic Arm for Reach and Grasp Tasks. Scientific Reports 6, https:\/\/doi.org\/10.1038\/srep38565 (2016).","DOI":"10.1038\/srep38565"},{"key":"6039_CR31","doi-asserted-by":"publisher","first-page":"e0182578","DOI":"10.1371\/journal.pone.0182578","volume":"12","author":"P Ofner","year":"2017","unstructured":"Ofner, P., Schwarz, A., Pereira, J. & M\u00fcller-Putz, G. R. Upper limb movements can be decoded from the time-domain of low-frequency EEG. PLoS ONE 12, e0182578\u2013e0182578, https:\/\/doi.org\/10.1371\/journal.pone.0182578 (2017).","journal-title":"PLoS ONE"},{"key":"6039_CR32","doi-asserted-by":"publisher","unstructured":"Cho, H., Ahn, M., Ahn, S., Moonyoung, K. & Jun, S. C. Supporting data for \u201cEEG datasets for motor imagery brain computer interface\u201d. https:\/\/doi.org\/10.5524\/100295 (2017).","DOI":"10.5524\/100295"},{"key":"6039_CR33","doi-asserted-by":"publisher","unstructured":"Ma, X., Qiu, S. & He, H. Multi-channel EEG recording during motor imagery of different joints from the same limb. Scientific Data 7, https:\/\/doi.org\/10.1038\/s41597-020-0535-2 (2020).","DOI":"10.1038\/s41597-020-0535-2"},{"key":"6039_CR34","doi-asserted-by":"publisher","unstructured":"Jeong, J.-H. et al. Multimodal signal dataset for 11 intuitive movement tasks from single upper extremity during multiple recording sessions. GigaScience 9, https:\/\/doi.org\/10.1093\/gigascience\/giaa098 (2020).","DOI":"10.1093\/gigascience\/giaa098"},{"key":"6039_CR35","doi-asserted-by":"publisher","unstructured":"Rasheed, S. & Mumtaz, W. Classification of Hand-Grasp Movements of Stroke Patients using EEG Data. 2021 International Conference on Artificial Intelligence (ICAI) 86\u201390, https:\/\/doi.org\/10.1109\/ICAI52203.2021.9445231 (2021).","DOI":"10.1109\/ICAI52203.2021.9445231"},{"key":"6039_CR36","doi-asserted-by":"publisher","unstructured":"Liu, H. et al. An EEG motor imagery dataset for brain computer interface in acute stroke patients. Scientific Data 11, https:\/\/doi.org\/10.1038\/s41597-023-02787-8 (2024).","DOI":"10.1038\/s41597-023-02787-8"},{"key":"6039_CR37","doi-asserted-by":"publisher","first-page":"153","DOI":"10.1016\/j.neuroimage.2005.12.003","volume":"31","author":"G Pfurtscheller","year":"2006","unstructured":"Pfurtscheller, G., Brunner, C., Schl\u00f6gl, A. & Lopes da Silva, F. H. Mu Rhythm (de)synchronization and EEG single-trial classification of different motor imagery tasks. NeuroImage 31, 153\u2013159, https:\/\/doi.org\/10.1016\/j.neuroimage.2005.12.003 (2006).","journal-title":"NeuroImage"},{"key":"6039_CR38","doi-asserted-by":"publisher","unstructured":"Yi, W. et al. EEG feature comparison and classification of simple and compound limb motor imagery. Journal of NeuroEngineering and Rehabilitation 10, https:\/\/doi.org\/10.1186\/1743-0003-10-106 (2013).","DOI":"10.1186\/1743-0003-10-106"},{"key":"6039_CR39","doi-asserted-by":"publisher","first-page":"4413","DOI":"10.1109\/tnsre.2023.3330500","volume":"31","author":"J Wang","year":"2023","unstructured":"Wang, J., Bi, L. & Fei, W. EEG-Based Motor BCIs for Upper Limb Movement: Current Techniques and Future Insights. IEEE Transactions on Neural Systems and Rehabilitation Engineering 31, 4413\u20134427, https:\/\/doi.org\/10.1109\/tnsre.2023.3330500 (2023).","journal-title":"IEEE Transactions on Neural Systems and Rehabilitation Engineering"},{"key":"6039_CR40","doi-asserted-by":"publisher","first-page":"2178","DOI":"10.1109\/TNSRE.2019.2936987","volume":"27","author":"MEM Mashat","year":"2019","unstructured":"Mashat, M. E. M., Lin, C.-T. & Zhang, D. Effects of Task Complexity on Motor Imagery-Based Brain\u2013Computer Interface. IEEE Transactions on Neural Systems and Rehabilitation Engineering 27, 2178\u20132185, https:\/\/doi.org\/10.1109\/TNSRE.2019.2936987 (2019).","journal-title":"IEEE Transactions on Neural Systems and Rehabilitation Engineering"},{"key":"6039_CR41","doi-asserted-by":"publisher","first-page":"e0144256","DOI":"10.1371\/journal.pone.0144256","volume":"10","author":"L Li","year":"2015","unstructured":"Li, L., Wang, J., Xu, G., Li, M. & Xie, J. The Study of Object-Oriented Motor Imagery Based on EEG Suppression. PLoS ONE 10, e0144256\u2013e0144256, https:\/\/doi.org\/10.1371\/journal.pone.0144256 (2015).","journal-title":"PLoS ONE"},{"key":"6039_CR42","doi-asserted-by":"publisher","unstructured":"Korik, A., Sosnik, R., Siddique, N. & Coyle, D. Decoding Imagined 3D Hand Movement Trajectories From EEG: Evidence to Support the Use of Mu, Beta, and Low Gamma Oscillations. Frontiers in Neuroscience 12, https:\/\/doi.org\/10.3389\/fnins.2018.00130 (2018).","DOI":"10.3389\/fnins.2018.00130"},{"key":"6039_CR43","doi-asserted-by":"publisher","first-page":"026001","DOI":"10.1088\/1741-2560\/7\/2\/026001","volume":"7","author":"H Yuan","year":"2010","unstructured":"Yuan, H., Perdoni, C. & He, B. Relationship between speed and EEG activity during imagined and executed hand movements. Journal of Neural Engineering 7, 026001\u2013026001, https:\/\/doi.org\/10.1088\/1741-2560\/7\/2\/026001 (2010).","journal-title":"Journal of Neural Engineering"},{"key":"6039_CR44","doi-asserted-by":"publisher","unstructured":"Luciw, M. D., Jarocka, E. & Edin, B. B. Multi-channel EEG recordings during 3,936 grasp and lift trials with varying weight and friction. Scientific Data 1, https:\/\/doi.org\/10.1038\/sdata.2014.47 (2014).","DOI":"10.1038\/sdata.2014.47"},{"key":"6039_CR45","doi-asserted-by":"publisher","unstructured":"Sburlea, A. I. & M\u00fcller-Putz, G. R. Exploring representations of human grasping in neural, muscle and kinematic signals. Scientific Reports 8, https:\/\/doi.org\/10.1038\/s41598-018-35018-x (2018).","DOI":"10.1038\/s41598-018-35018-x"},{"key":"6039_CR46","doi-asserted-by":"publisher","unstructured":"Schwarz, A., Escolano, C., Montesano, L. & M\u00fcller-Putz, G. R. Analyzing and Decoding Natural Reach-and-Grasp Actions Using Gel, Water and Dry EEG Systems. Frontiers in Neuroscience 14, https:\/\/doi.org\/10.3389\/fnins.2020.00849 (2020).","DOI":"10.3389\/fnins.2020.00849"},{"key":"6039_CR47","doi-asserted-by":"publisher","first-page":"178","DOI":"10.1080\/2326263X.2019.1697143","volume":"6","author":"F Lotte","year":"2019","unstructured":"Lotte, F. et al. Turning negative into positives! Exploiting \u2018negative\u2019 results in Brain\u2013Machine Interface (BMI) research. Brain-Computer Interfaces 6, 178\u2013189, https:\/\/doi.org\/10.1080\/2326263X.2019.1697143 (2019).","journal-title":"Brain-Computer Interfaces"},{"key":"6039_CR48","doi-asserted-by":"publisher","first-page":"031005","DOI":"10.1088\/1741-2552\/aab2f2","volume":"15","author":"F Lotte","year":"2018","unstructured":"Lotte, F. et al. A review of classification algorithms for EEG-based brain\u2013computer interfaces: a 10 year update. Journal of Neural Engineering 15, 031005\u2013031005, https:\/\/doi.org\/10.1088\/1741-2552\/aab2f2 (2018).","journal-title":"Journal of Neural Engineering"},{"key":"6039_CR49","doi-asserted-by":"publisher","unstructured":"Bhagat, N. A. et al. Design and Optimization of an EEG-Based Brain Machine Interface (BMI) to an Upper-Limb Exoskeleton for Stroke Survivors. Frontiers in Neuroscience 10, https:\/\/doi.org\/10.3389\/fnins.2016.00122 (2016).","DOI":"10.3389\/fnins.2016.00122"},{"key":"6039_CR50","doi-asserted-by":"publisher","first-page":"163","DOI":"10.1111\/1469-8986.3720163","volume":"37","author":"T Jung","year":"2000","unstructured":"Jung, T. et al. Removing electroencephalographic artifacts by blind source separation. Psychophysiology 37, 163\u2013178 (2000).","journal-title":"Psychophysiology"},{"key":"6039_CR51","doi-asserted-by":"publisher","first-page":"468","DOI":"10.1016\/0013-4694(83)90135-9","volume":"55","author":"G Gratton","year":"1983","unstructured":"Gratton, G., Coles, M. G. H. & Donchin, E. A new method for off-line removal of ocular artifact. Electroencephalography and Clinical Neurophysiology 55, 468\u2013484, https:\/\/doi.org\/10.1016\/0013-4694(83)90135-9 (1983).","journal-title":"Electroencephalography and Clinical Neurophysiology"},{"key":"6039_CR52","doi-asserted-by":"publisher","first-page":"987","DOI":"10.3390\/s19050987","volume":"19","author":"X Jiang","year":"2019","unstructured":"Jiang, X., Bian, G.-B. & Tian, Z. Removal of Artifacts from EEG Signals: A Review. Sensors 19, 987\u2013987, https:\/\/doi.org\/10.3390\/s19050987 (2019).","journal-title":"Sensors"},{"key":"6039_CR53","doi-asserted-by":"publisher","first-page":"012093","DOI":"10.1088\/1742-6596\/1706\/1\/012093","volume":"1706","author":"S Kotte","year":"2020","unstructured":"Kotte, S. & Kumar, K. Methods for removal of artifacts from EEG signal: A review. Journal of Physics Conference Series 1706, 012093\u2013012093, https:\/\/doi.org\/10.1088\/1742-6596\/1706\/1\/012093 (2020).","journal-title":"Journal of Physics Conference Series"},{"key":"6039_CR54","doi-asserted-by":"publisher","first-page":"960","DOI":"10.1016\/j.bbe.2021.06.007","volume":"41","author":"R Ranjan","year":"2021","unstructured":"Ranjan, R., Chandra Sahana, B. & Kumar Bhandari, A. Ocular artifact elimination from electroencephalography signals: A systematic review. Biocybernetics and Biomedical Engineering 41, 960\u2013996, https:\/\/doi.org\/10.1016\/j.bbe.2021.06.007 (2021).","journal-title":"Biocybernetics and Biomedical Engineering"},{"key":"6039_CR55","doi-asserted-by":"publisher","first-page":"16","DOI":"10.1111\/j.1468-8986.2005.00264.x","volume":"42","author":"RJ Croft","year":"2005","unstructured":"Croft, R. J., Chandler, J. S., Barry, R. J., Cooper, N. R. & Clarke, A. R. EOG correction: A comparison of four methods. Psychophysiology 42, 16\u201324, https:\/\/doi.org\/10.1111\/j.1468-8986.2005.00264.x (2005).","journal-title":"Psychophysiology"},{"key":"6039_CR56","doi-asserted-by":"publisher","unstructured":"Hooks, K., El-Said, R. & Fu, Q. Decoding reach-to-grasp from EEG using classifiers trained with data from the contralateral limb. Frontiers in Human Neuroscience 17, https:\/\/doi.org\/10.3389\/fnhum.2023.1302647 (2023).","DOI":"10.3389\/fnhum.2023.1302647"},{"key":"6039_CR57","doi-asserted-by":"publisher","first-page":"3095","DOI":"10.1007\/s00521-016-2578-z","volume":"28","author":"M Dursun","year":"2016","unstructured":"Dursun, M. et al. A new approach to eliminating EOG artifacts from the sleep EEG signals for the automatic sleep stage classification. Neural Computing and Applications 28, 3095\u20133112, https:\/\/doi.org\/10.1007\/s00521-016-2578-z (2016).","journal-title":"Neural Computing and Applications"},{"key":"6039_CR58","doi-asserted-by":"publisher","unstructured":"Wu, J., Zhang, J. & Yao, L. An automated detection and correction method of EOG artifacts in EEG-based BCI. https:\/\/doi.org\/10.1109\/iccme.2009.4906624 (2009).","DOI":"10.1109\/iccme.2009.4906624"},{"key":"6039_CR59","doi-asserted-by":"publisher","first-page":"59","DOI":"10.1016\/0926-6410(95)00046-1","volume":"3","author":"L Deecke","year":"1996","unstructured":"Deecke, L. Planning, preparation, execution, and imagery of volitional action. Cognitive Brain Research 3, 59\u201364, https:\/\/doi.org\/10.1016\/0926-6410(95)00046-1 (1996).","journal-title":"Cognitive Brain Research"},{"key":"6039_CR60","doi-asserted-by":"publisher","first-page":"614","DOI":"10.1016\/j.neubiorev.2014.10.003","volume":"47","author":"LM Rueda-Delgado","year":"2014","unstructured":"Rueda-Delgado, L. M. et al. Understanding bimanual coordination across small time scales from an electrophysiological perspective. Neuroscience & Biobehavioral Reviews 47, 614\u2013635, https:\/\/doi.org\/10.1016\/j.neubiorev.2014.10.003 (2014).","journal-title":"Neuroscience & Biobehavioral Reviews"},{"key":"6039_CR61","doi-asserted-by":"publisher","unstructured":"M\u00fcller-Putz, G. R. et al. Feel Your Reach: An EEG-Based Framework to Continuously Detect Goal-Directed Movements and Error Processing to Gate Kinesthetic Feedback Informed Artificial Arm Control. Frontiers in Human Neuroscience 16, https:\/\/doi.org\/10.3389\/fnhum.2022.841312 (2022).","DOI":"10.3389\/fnhum.2022.841312"},{"key":"6039_CR62","doi-asserted-by":"publisher","unstructured":"Hurst, A. J. & Boe, S. G. Imagining the way forward: A review of contemporary motor imagery theory. Frontiers in Human Neuroscience 16, https:\/\/doi.org\/10.3389\/fnhum.2022.1033493 (2022).","DOI":"10.3389\/fnhum.2022.1033493"},{"key":"6039_CR63","doi-asserted-by":"publisher","first-page":"422","DOI":"10.3390\/electronics9030422","volume":"9","author":"C-H Han","year":"2020","unstructured":"Han, C.-H., M\u00fcller, K.-R. & Hwang, H.-J. Brain-Switches for Asynchronous Brain\u2013Computer Interfaces: A Systematic Review. Electronics 9, 422\u2013422, https:\/\/doi.org\/10.3390\/electronics9030422 (2020).","journal-title":"Electronics"},{"key":"6039_CR64","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/tnsre.2003.814454","volume":"11","author":"G Pfurtscheller","year":"2003","unstructured":"Pfurtscheller, G. et al. Graz-BCI: state of the art and clinical applications. IEEE Transactions on Neural Systems and Rehabilitation Engineering 11, 1\u20134, https:\/\/doi.org\/10.1109\/tnsre.2003.814454 (2003).","journal-title":"IEEE Transactions on Neural Systems and Rehabilitation Engineering"},{"key":"6039_CR65","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1155\/2020\/8573754","volume":"2020","author":"S Rodpongpun","year":"2020","unstructured":"Rodpongpun, S., Janyalikit, T. & Ratanamahatana, C. A. Influential Factors of an Asynchronous BCI for Movement Intention Detection. Computational and Mathematical Methods in Medicine 2020, 1\u201312, https:\/\/doi.org\/10.1155\/2020\/8573754 (2020).","journal-title":"Computational and Mathematical Methods in Medicine"},{"key":"6039_CR66","doi-asserted-by":"publisher","unstructured":"Sun, S., Cao, X. & Wang, Q. Continuous decoding of movement onset and offset of sustained movements from cortical activities. 2022 IEEE\/SICE International Symposium on System Integration (SII) 809\u2013814, https:\/\/doi.org\/10.1109\/SII.2016.7844099 (2016).","DOI":"10.1109\/SII.2016.7844099"},{"key":"6039_CR67","doi-asserted-by":"publisher","unstructured":"Thapa, B. R., Boggess, J. & Bae, J. A Large Electroencephalogram Database of Freewill Reaching and Grasping Tasks for Brain Machine Interfaces. Figshare https:\/\/doi.org\/10.6084\/m9.figshare.28632599 (2025).","DOI":"10.6084\/m9.figshare.28632599"},{"key":"6039_CR68","doi-asserted-by":"publisher","unstructured":"Pernet, C. R. et al. EEG-BIDS, an extension to the brain imaging data structure for electroencephalography. Scientific Data 6, https:\/\/doi.org\/10.1038\/s41597-019-0104-8 (2019).","DOI":"10.1038\/s41597-019-0104-8"},{"key":"6039_CR69","doi-asserted-by":"publisher","first-page":"261","DOI":"10.1038\/s41592-019-0686-2","volume":"17","author":"P Virtanen","year":"2020","unstructured":"Virtanen, P. et al. SciPy 1.0: fundamental algorithms for scientific computing in Python. Nature Methods 17, 261\u2013272, https:\/\/doi.org\/10.1038\/s41592-019-0686-2 (2020).","journal-title":"Nature Methods"},{"key":"6039_CR70","doi-asserted-by":"publisher","first-page":"291","DOI":"10.1016\/j.bspc.2011.02.001","volume":"6","author":"MA Klados","year":"2011","unstructured":"Klados, M. A., Papadelis, C., Braun, C. & Bamidis, P. D. REG-ICA: A hybrid methodology combining Blind Source Separation and regression techniques for the rejection of ocular artifacts. Biomedical Signal Processing and Control 6, 291\u2013300, https:\/\/doi.org\/10.1016\/j.bspc.2011.02.001 (2011).","journal-title":"Biomedical Signal Processing and Control"},{"key":"6039_CR71","doi-asserted-by":"publisher","first-page":"1370","DOI":"10.1109\/tnn.2006.880980","volume":"17","author":"E Oja","year":"2006","unstructured":"Oja, E. & Yuan, N. Z. The FastICA Algorithm Revisited: Convergence Analysis. IEEE Transactions on Neural Networks 17, 1370\u20131381, https:\/\/doi.org\/10.1109\/tnn.2006.880980 (2006).","journal-title":"IEEE Transactions on Neural Networks"},{"key":"6039_CR72","doi-asserted-by":"publisher","first-page":"417","DOI":"10.1162\/089976699300016719","volume":"11","author":"T-W Lee","year":"1999","unstructured":"Lee, T.-W., Girolami, M. & Sejnowski, T. J. Independent Component Analysis Using an Extended Infomax Algorithm for Mixed Subgaussian and Supergaussian Sources. Neural Computation 11, 417\u2013441, https:\/\/doi.org\/10.1162\/089976699300016719 (1999).","journal-title":"Neural Computation"},{"key":"6039_CR73","doi-asserted-by":"publisher","unstructured":"Tang, Y., Tang, J. & Gong, A. Removal of Ocular Artifact from EEG Using JADE. 39, 566\u2013569, https:\/\/doi.org\/10.1016\/s0987-7053(00)00055-1 (2007).","DOI":"10.1016\/s0987-7053(00)00055-1"},{"key":"6039_CR74","doi-asserted-by":"publisher","first-page":"031001","DOI":"10.1088\/1741-2560\/12\/3\/031001","volume":"12","author":"JA Urig\u00fcen","year":"2015","unstructured":"Urig\u00fcen, J. A. & Garcia-Zapirain, B. EEG artifact removal\u2014state-of-the-art and guidelines. Journal of Neural Engineering 12, 031001\u2013031001, https:\/\/doi.org\/10.1088\/1741-2560\/12\/3\/031001 (2015).","journal-title":"Journal of Neural Engineering"},{"key":"6039_CR75","doi-asserted-by":"publisher","first-page":"348","DOI":"10.1016\/j.compbiomed.2007.12.001","volume":"38","author":"S Romero","year":"2008","unstructured":"Romero, S., Ma\u00f1anas, M. A. & Barbanoj, M. J. A comparative study of automatic techniques for ocular artifact reduction in spontaneous EEG signals based on clinical target variables: A simulation case. Computers in Biology and Medicine 38, 348\u2013360, https:\/\/doi.org\/10.1016\/j.compbiomed.2007.12.001 (2008).","journal-title":"Computers in Biology and Medicine"},{"key":"6039_CR76","doi-asserted-by":"publisher","first-page":"407","DOI":"10.2478\/v10175-012-0052-3","volume":"60","author":"L Albera","year":"2012","unstructured":"Albera, L. et al. ICA-Based EEG denoising: a comparative analysis of fifteen methods. Bulletin of the Polish Academy of Sciences: Technical Sciences 60, 407\u2013418, https:\/\/doi.org\/10.2478\/v10175-012-0052-3 (2012).","journal-title":"Bulletin of the Polish Academy of Sciences: Technical Sciences"},{"key":"6039_CR77","unstructured":"Plank, M. Ocular Correction ICA. Brain Products GmbH https:\/\/www.brainproducts.com\/support-resources\/ocular-correction-ica\/ (2022)."},{"key":"6039_CR78","doi-asserted-by":"publisher","first-page":"108746","DOI":"10.1016\/j.neuropsychologia.2023.108746","volume":"193","author":"S Noviello","year":"2023","unstructured":"Noviello, S. et al. Temporal features of size constancy for perception and action in a real-world setting: A combined EEG-kinematics study. Neuropsychologia 193, 108746\u2013108746, https:\/\/doi.org\/10.1016\/j.neuropsychologia.2023.108746 (2023).","journal-title":"Neuropsychologia"},{"key":"6039_CR79","doi-asserted-by":"publisher","unstructured":"Lew, E, Chavarriaga, R., Silvoni, S. & Mill\u00e1n, J. D. R. Detection of self-paced reaching movement intention from EEG signals. Frontiers in Neuroengineering 5, https:\/\/doi.org\/10.3389\/fneng.2012.00013 (2012).","DOI":"10.3389\/fneng.2012.00013"},{"key":"6039_CR80","doi-asserted-by":"publisher","unstructured":"Kuo, N. C.-C., Lin, W. S., Dressel, C. A. & Chiu, L. Classification of intended motor movement using surface EEG ensemble empirical mode decomposition. Annual International Conference of the IEEE Engineering in Medicine and Biology Society 6281\u20136284, https:\/\/doi.org\/10.1109\/IEMBS.2011.6091550 (2011).","DOI":"10.1109\/IEMBS.2011.6091550"},{"key":"6039_CR81","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1155\/2015\/346217","volume":"2015","author":"A Shakeel","year":"2015","unstructured":"Shakeel, A. et al. A Review of Techniques for Detection of Movement Intention Using Movement-Related Cortical Potentials. Computational and Mathematical Methods in Medicine 2015, 1\u201313, https:\/\/doi.org\/10.1155\/2015\/346217 (2015).","journal-title":"Computational and Mathematical Methods in Medicine"},{"key":"6039_CR82","doi-asserted-by":"publisher","first-page":"601","DOI":"10.1002\/mds.21323","volume":"22","author":"JG Colebatch","year":"2007","unstructured":"Colebatch, J. G. Bereitschaftspotential and movement-related potentials: Origin, significance, and application in disorders of human movement. Movement Disorders 22, 601\u2013610, https:\/\/doi.org\/10.1002\/mds.21323 (2007).","journal-title":"Movement Disorders"},{"key":"6039_CR83","doi-asserted-by":"publisher","first-page":"3894","DOI":"10.3390\/electronics12183894","volume":"12","author":"H Gu","year":"2023","unstructured":"Gu, H. et al. Decoding Electroencephalography Underlying Natural Grasp Tasks across Multiple Dimensions. Electronics 12, 3894\u20133894, https:\/\/doi.org\/10.3390\/electronics12183894 (2023).","journal-title":"Electronics"},{"key":"6039_CR84","doi-asserted-by":"publisher","first-page":"1842","DOI":"10.1016\/s1388-2457(99)00141-8","volume":"110","author":"G Pfurtscheller","year":"1999","unstructured":"Pfurtscheller, G. & Lopes da Silva, F. H. Event-related EEG\/MEG synchronization and desynchronization: basic principles. Clinical Neurophysiology 110, 1842\u20131857, https:\/\/doi.org\/10.1016\/s1388-2457(99)00141-8 (1999).","journal-title":"Clinical Neurophysiology"},{"key":"6039_CR85","doi-asserted-by":"publisher","first-page":"1962","DOI":"10.1111\/ejn.14629","volume":"51","author":"AM Savi\u0107","year":"2019","unstructured":"Savi\u0107, A. M., Lontis, E. R., Mrachacz-Kersting, N. & Popovi\u0107, M. B. Dynamics of movement-related cortical potentials and sensorimotor oscillations during palmar grasp movements. European Journal of Neuroscience 51, 1962\u20131970, https:\/\/doi.org\/10.1111\/ejn.14629 (2019).","journal-title":"European Journal of Neuroscience"},{"key":"6039_CR86","doi-asserted-by":"publisher","first-page":"046050","DOI":"10.1088\/1741-2552\/ac86f5","volume":"19","author":"M Borr\u00e0s","year":"2022","unstructured":"Borr\u00e0s, M. et al. Influence of the number of trials on evoked motor cortical activity in EEG recordings. Journal of Neural Engineering 19, 046050, https:\/\/doi.org\/10.1088\/1741-2552\/ac86f5 (2022).","journal-title":"Journal of Neural Engineering"},{"key":"6039_CR87","doi-asserted-by":"publisher","first-page":"835","DOI":"10.3390\/make3040042","volume":"3","author":"S Rasheed","year":"2021","unstructured":"Rasheed, S. A Review of the Role of Machine Learning Techniques towards Brain\u2013Computer Interface Applications. Machine Learning and Knowledge Extraction 3, 835\u2013862, https:\/\/doi.org\/10.3390\/make3040042 (2021).","journal-title":"Machine Learning and Knowledge Extraction"},{"key":"6039_CR88","doi-asserted-by":"publisher","first-page":"1525","DOI":"10.3390\/brainsci11111525","volume":"11","author":"M Saeidi","year":"2021","unstructured":"Saeidi, M. et al. Neural Decoding of EEG Signals with Machine Learning: A Systematic Review. Brain Sciences 11, 1525, https:\/\/doi.org\/10.3390\/brainsci11111525 (2021).","journal-title":"Brain Sciences"},{"key":"6039_CR89","first-page":"101","volume":"5","author":"R Rifkin","year":"2004","unstructured":"Rifkin, R. & Klautau, A. In Defense of One-Vs-All Classification. Journal of Machine Learning Research 5, 101\u2013141 (2004).","journal-title":"Journal of Machine Learning Research"},{"key":"6039_CR90","doi-asserted-by":"publisher","first-page":"01","DOI":"10.5121\/ijdkp.2015.5201","volume":"5","author":"M Hossin","year":"2015","unstructured":"Hossin, M. & Sulaiman, M. N. A Review on Evaluation Metrics for Data Classification Evaluations. International Journal of Data Mining & Knowledge Management Process 5, 01\u201311, https:\/\/doi.org\/10.5121\/ijdkp.2015.5201 (2015).","journal-title":"International Journal of Data Mining & Knowledge Management Process"}],"container-title":["Scientific Data"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s41597-025-06039-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41597-025-06039-9","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41597-025-06039-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,7]],"date-time":"2025-11-07T10:54:01Z","timestamp":1762512841000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s41597-025-06039-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,7]]},"references-count":90,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025,12]]}},"alternative-id":["6039"],"URL":"https:\/\/doi.org\/10.1038\/s41597-025-06039-9","relation":{},"ISSN":["2052-4463"],"issn-type":[{"value":"2052-4463","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,11,7]]},"assertion":[{"value":"26 March 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"25 September 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 November 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The authors declare no competing interests.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"1760"}}