{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/a-plugplay-p300-bci-using-information","title":"A Plug&Play P300 BCI Using Information Geometry","arxiv_id":"1409.0107","date":"2014-08-30","proceeding":null,"authors":["Alexandre Barachant","Marco Congedo"],"abstract":"This paper presents a new classification methods for Event Related Potentials\n(ERP) based on an Information geometry framework. Through a new estimation of\ncovariance matrices, this work extend the use of Riemannian geometry, which was\npreviously limited to SMR-based BCI, to the problem of classification of ERPs.\nAs compared to the state-of-the-art, this new method increases performance,\nreduces the number of data needed for the calibration and features good\ngeneralisation across sessions and subjects. This method is illustrated on data\nrecorded with the P300-based game brain invaders. Finally, an online and\nadaptive implementation is described, where the BCI is initialized with generic\nparameters derived from a database and continuously adapt to the individual,\nallowing the user to play the game without any calibration while keeping a high\naccuracy.","url_abs":"http://arxiv.org/abs/1409.0107v1","url_pdf":"http://arxiv.org/pdf/1409.0107v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"a-plugplay-p300-bci-using-information","repo_url":"https://github.com/LauraMasiero/RiemannR","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"a-plugplay-p300-bci-using-information","repo_url":"https://github.com/alexandrebarachant/bci-challenge-ner-2015","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"a-plugplay-p300-bci-using-information","repo_url":"https://github.com/alexandrebarachant/pyRiemann","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"a-plugplay-p300-bci-using-information","repo_url":"https://github.com/pyRiemann/pyRiemann","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"erp","task_name":"ERP"},{"task_slug":"classification","task_name":"General Classification"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}