{"id":24189419,"url":"https://github.com/okbalefthanded/bci_toolbox","last_synced_at":"2025-06-21T08:07:53.455Z","repository":{"id":133913760,"uuid":"118654065","full_name":"okbalefthanded/bci_toolbox","owner":"okbalefthanded","description":"Classification toolbox for ERP and SSVEP based BCI data ","archived":false,"fork":false,"pushed_at":"2021-05-03T23:45:05.000Z","size":7331,"stargazers_count":53,"open_issues_count":5,"forks_count":27,"subscribers_count":4,"default_branch":"master","last_synced_at":"2025-06-08T09:05:16.338Z","etag":null,"topics":["benchmarking","brain-computer-interface","classification","eeg","erp","machine-learning","ssvep"],"latest_commit_sha":null,"homepage":"","language":"MATLAB","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/okbalefthanded.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null}},"created_at":"2018-01-23T18:51:01.000Z","updated_at":"2025-04-23T04:32:03.000Z","dependencies_parsed_at":null,"dependency_job_id":"5b173c78-be3e-4266-ad37-ad427914f9be","html_url":"https://github.com/okbalefthanded/bci_toolbox","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/okbalefthanded/bci_toolbox","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/okbalefthanded%2Fbci_toolbox","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/okbalefthanded%2Fbci_toolbox/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/okbalefthanded%2Fbci_toolbox/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/okbalefthanded%2Fbci_toolbox/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/okbalefthanded","download_url":"https://codeload.github.com/okbalefthanded/bci_toolbox/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/okbalefthanded%2Fbci_toolbox/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":261088356,"owners_count":23107683,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["benchmarking","brain-computer-interface","classification","eeg","erp","machine-learning","ssvep"],"created_at":"2025-01-13T14:29:36.068Z","updated_at":"2025-06-21T08:07:48.441Z","avatar_url":"https://github.com/okbalefthanded.png","language":"MATLAB","funding_links":[],"categories":[],"sub_categories":[],"readme":"# bci_toolbox (work in Progress)\n\nA benchamark classification toolbox for Brain-Computer Interface EEG data\n\n Data sets available:\n \n ## ERP Data sets:\n  1. BCI Compeition III Challenge 2004 (P300 evoked potentials) (http://www.bbci.de/competition/iii/)\n  2. EPFL P300 data set (https://mmspg.epfl.ch/BCI_datasets)\n  3. P300 speller with ALS patients (set #8) (http://bnci-horizon-2020.eu/database/data-sets)\n  4. LARESI inverted face data set (coming soon)\n\n## SSVEP Data sets:\n  1. SSVEP Exoskeleton (https://old.datahub.io/dataset/dataset-ssvep-exoskeleton)\n  2. Tsinghua Sampled sinusoidal Joint Frequency-Phase Modulation SSVEP (http://www.thubci.org/en/?a=nr\u0026id=100)\n  3. San Diego Square Joint Frequnecy-Phase Modulation SSVEP (ftp://sccn.ucsd.edu/pub/cca_ssvep)\n\n\n- Processing methods available: \n\n- - Feature extraction: \n    --- Downsample\n    --- Multivariate Linear Regression(MLR)\n- - classification : \n  - - - LDA\n  - - - Regularized LDA (shrinkage-LDA)\n  - - - SWDLA\n  - - - SVM (LIBSVM)\n  - - - Logistic Regression (LIBLINEAR)\n  - - - Random Forest \n  - - - SVM+ \n  - - - Canonical Correlation Analysis based methods : \n               - - - CCA, FilterBank CCA (FBCCA), L1-Multiway CCA, MsetCCA, Individual Template CCA (ITCCA)\n  - - - Task-related Component Analysis (TRCA)\n  \n  \n  # Setup\n  Run the setup.m script\n  \n  # Usage\n  ## First run\n  - Download one of the Datasets (or all) in the list.\n  - create a new folder inside the Dataset/epochs.\n  - Run one (or all, one by one) scripts related to each dataset in the dataio folder.\n  \n  ## Regular usage\n  - Run the script \"define_approach_ERP.m\" for ERP data\n  - Run the script \"define_approach_SSVEP.m\" for SSVEP data\n  \n  # Documentation\n  coming soon\n  \n  # Cite us\n  coming soon\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fokbalefthanded%2Fbci_toolbox","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fokbalefthanded%2Fbci_toolbox","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fokbalefthanded%2Fbci_toolbox/lists"}