{"dataset":{"id":"155","dataset_id":"nm000140","name":"BNCI 2015-001 Motor Imagery dataset","description":"A two-class motor imagery EEG dataset comprising 12 healthy, right-handed naive subjects performing sustained kinesthetic imagery of right-hand palmar grip versus bilateral feet plantar extension. The dataset includes 2 sessions per subject with 200 trials total (100 per class), recorded at 512 Hz from 13 EEG channels using g.tec hardware with visual and auditory feedback. Data were preprocessed with bandpass filtering (0.5-100 Hz) and notch filtering at 50 Hz, achieving 80% classification accuracy with LDA and Common Spatial Patterns features.","owner_user_id":19,"status":"active","github_repo":"nemarDatasets/nm000140","concept_doi":"10.82901/nemar.nm000140","latest_version_doi":"10.82901/nemar.nm000140.v1.0.2","created_at":"2026-03-17 22:03:14","updated_at":"2026-08-18 18:11:04","zenodo_concept_id":"19632030","is_sandbox":0,"visibility":"public","ezid_status":"public","enrichment_json":"{\n  \"version\": \"2.0\",\n  \"pipeline_stage\": \"validated\",\n  \"title\": \"BNCI 2015-001 Motor Imagery dataset\",\n  \"description\": \"A two-class motor imagery EEG dataset comprising 12 healthy, right-handed naive subjects performing sustained kinesthetic imagery of right-hand palmar grip versus bilateral feet plantar extension. The dataset includes 2 sessions per subject with 200 trials total (100 per class), recorded at 512 Hz from 13 EEG channels using g.tec hardware with visual and auditory feedback. Data were preprocessed with bandpass filtering (0.5-100 Hz) and notch filtering at 50 Hz, achieving 80% classification accuracy with LDA and Common Spatial Patterns features.\",\n  \"methods_description\": \"EEG data were acquired at 512 Hz from 13 active electrodes (FC3, FCz, FC4, C5, C3, C1, Cz, C2, C4, C6, CP3, CPz, CP4) using g.tec g.GAMMAsys cap with 10-20 montage. Online 50 Hz notch filtering was applied. Preprocessing included bandpass filtering (0.5-100 Hz) and common average re-referencing. Subjects performed two-class motor imagery tasks with visual cursor feedback: right-hand palmar grip imagery (1.25 s cue, 4 s imagery) versus bilateral feet plantar extension imagery. Each session contained 100 trials per class.\",\n  \"license\": \"CC-BY-NC-ND-4.0\",\n  \"dataset_type\": \"derivative\",\n  \"authors\": {\n    \"Josef Faller\": {},\n    \"Carmen Vidaurre\": {},\n    \"Teodoro Solis-Escalante\": {},\n    \"Christa Neuper\": {},\n    \"Reinhold Scherer\": {}\n  },\n  \"keywords\": [\n    {\n      \"term\": \"EEG\"\n    },\n    {\n      \"term\": \"motor imagery\"\n    },\n    {\n      \"term\": \"brain-computer interfaces\"\n    },\n    {\n      \"term\": \"Common Spatial Patterns\"\n    },\n    {\n      \"term\": \"event-related desynchronization\"\n    },\n    {\n      \"term\": \"kinesthetic imagery\"\n    }\n  ],\n  \"related_identifiers\": [\n    {\n      \"identifier\": \"10.1109/tnsre.2012.2189584\",\n      \"identifier_type\": \"DOI\",\n      \"relation_type\": \"IsDerivedFrom\"\n    },\n    {\n      \"identifier\": \"https://github.com/nemarDatasets/nm000140\",\n      \"identifier_type\": \"URL\",\n      \"relation_type\": \"IsDescribedBy\"\n    },\n    {\n      \"identifier\": \"10.21105/joss.01896\",\n      \"identifier_type\": \"DOI\",\n      \"relation_type\": \"References\"\n    },\n    {\n      \"identifier\": \"10.1038/s41597-019-0104-8\",\n      \"identifier_type\": \"DOI\",\n      \"relation_type\": \"References\"\n    },\n    {\n      \"identifier\": \"https://nemar.org/dataset/nm000140\",\n      \"identifier_type\": \"URL\",\n      \"relation_type\": \"IsDescribedBy\"\n    }\n  ],\n  \"funding_references\": [\n    {\n      \"funder_name\": \"European Commission\",\n      \"award_number\": \"247447\",\n      \"award_title\": \"BrainAble\"\n    }\n  ],\n  \"resource_type_general\": \"Dataset\",\n  \"resource_type_specific\": \"EEG Dataset\",\n  \"modalities\": [\n    \"eeg\"\n  ],\n  \"sizes\": [\n    \"3.0 GB (59 files)\"\n  ],\n  \"formats\": [\n    \".bdf\",\n    \".html\",\n    \".json\",\n    \".mat\",\n    \".md\",\n    \".tsv\",\n    \".yaml\",\n    \".yml\"\n  ],\n  \"source_hash\": \"766e98de3e1e3c7c9d340b32f88064729d4de1b71eb23b4206856e69f84f0ba8\"\n}","last_activity_at":"2026-08-16 13:27:24","source":null,"source_id":null,"subject_count":12,"modalities":"eeg","age_min":24.8,"age_max":24.8,"file_size":3042589065,"total_files":349,"tasks":"imagery","metadata_columns_error":null,"staleness_warn_stage":null,"staleness_admin_notified_at":null,"authors":"Josef Faller, Carmen Vidaurre, Teodoro Solis-Escalante, Christa Neuper, Reinhold Scherer","license":"CC-BY-NC-ND-4.0","readme":"[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.nm000140-blue)](https://doi.org/10.82901/nemar.nm000140)\n\n# BNCI 2015-001 Motor Imagery dataset\n\nBNCI 2015-001 Motor Imagery dataset.\n\n## Dataset Overview\n\n- **Code**: BNCI2015-001\n- **Paradigm**: imagery\n- **DOI**: 10.1109/tnsre.2012.2189584\n- **Subjects**: 12\n- **Sessions per subject**: 2\n- **Events**: right_hand=1, feet=2\n- **Trial interval**: [0, 5] s\n- **File format**: gdf\n- **Data preprocessed**: True\n\n## Acquisition\n\n- **Sampling rate**: 512.0 Hz\n- **Number of channels**: 13\n- **Channel types**: eeg=13\n- **Channel names**: FC3, FCz, FC4, C5, C3, C1, Cz, C2, C4, C6, CP3, CPz, CP4\n- **Montage**: 10-20\n- **Hardware**: g.tec\n- **Software**: Matlab\n- **Reference**: Car\n- **Sensor type**: active electrode\n- **Line frequency**: 50.0 Hz\n- **Online filters**: 50 Hz notch\n- **Cap manufacturer**: g.tec\n- **Cap model**: g.GAMMAsys\n- **Auxiliary channels**: gsr\n\n## Participants\n\n- **Number of subjects**: 12\n- **Health status**: healthy\n- **Age**: mean=24.8\n- **Gender distribution**: male=7, female=5\n- **Handedness**: all right-handed\n- **BCI experience**: naive\n- **Species**: human\n\n## Experimental Protocol\n\n- **Paradigm**: imagery\n- **Number of classes**: 2\n- **Class labels**: right_hand, feet\n- **Trial duration**: 11.0 s\n- **Study design**: Two-class motor imagery: sustained right hand movement imagery (palmar grip) versus both feet movement imagery (plantar extension)\n- **Feedback type**: visual\n- **Stimulus type**: cursor_feedback\n- **Stimulus modalities**: visual, auditory\n- **Primary modality**: visual\n- **Synchronicity**: synchronous\n- **Mode**: training\n- **Instructions**: Relax during reference period (3s), perform sustained kinesthetic movement imagery during activity period. Condition 1 (arrow right): imagine palmar grip with right hand. Condition 2 (arrow down): imagine plantar extension of both feet.\n\n## HED Event Annotations\n\nSchema: HED 8.4.0 | Browse: https://www.hedtags.org/hed-schema-browser\n\n```\n  right_hand\n    ├─ Sensory-event, Experimental-stimulus, Visual-presentation\n    └─ Agent-action\n       └─ Imagine\n          ├─ Move\n          └─ Right, Hand\n\n  feet\n    ├─ Sensory-event, Experimental-stimulus, Visual-presentation\n    └─ Agent-action\n       └─ Imagine, Move, Foot\n\n```\n## Paradigm-Specific Parameters\n\n- **Detected paradigm**: motor_imagery\n- **Imagery tasks**: right_hand_palmar_grip, both_feet_plantar_extension\n- **Cue duration**: 1.25 s\n- **Imagery duration**: 4.0 s\n\n## Data Structure\n\n- **Trials**: 200\n- **Trials per class**: right_hand=100, feet=100\n- **Trials context**: per_session\n\n## Preprocessing\n\n- **Data state**: filtered\n- **Preprocessing applied**: True\n- **Steps**: bandpass filter, notch filter\n- **Highpass filter**: 0.5 Hz\n- **Lowpass filter**: 100.0 Hz\n- **Bandpass filter**: {'low_cutoff_hz': 0.5, 'high_cutoff_hz': 100.0}\n- **Notch filter**: [50.0] Hz\n- **Re-reference**: car\n\n## Signal Processing\n\n- **Classifiers**: LDA\n- **Feature extraction**: logarithmic bandpower, CSP\n- **Frequency bands**: alpha=[10, 13] Hz; beta=[16, 24] Hz\n\n## Cross-Validation\n\n- **Method**: leave-one-out\n- **Evaluation type**: cross_session\n\n## Performance (Original Study)\n\n- **Accuracy**: 80.0%\n\n## BCI Application\n\n- **Applications**: communication, control\n- **Online feedback**: True\n\n## Tags\n\n- **Pathology**: Healthy\n- **Modality**: Motor\n- **Type**: Motor\n\n## Documentation\n\n- **DOI**: 10.1109/tnsre.2012.2189584\n- **License**: CC-BY-NC-ND-4.0\n- **Investigators**: Josef Faller, Carmen Vidaurre, Teodoro Solis-Escalante, Christa Neuper, Reinhold Scherer\n- **Senior author**: Reinhold Scherer\n- **Contact**: josef.faller@tugraz.at; christa.neuper@uni-graz.at; carmen.vidaurre@tu-berlin.de\n- **Institution**: Graz University of Technology\n- **Department**: Institute of Knowledge Discovery\n- **Address**: 8010 Graz, Austria\n- **Country**: Austria\n- **Repository**: BNCI Horizon\n- **Publication year**: 2012\n- **Funding**: FP7 Framework EU Research Project BrainAble (No. 247447)\n\n## References\n\nFaller, J., Vidaurre, C., Solis-Escalante, T., Neuper, C., & Scherer, R. (2012). Autocalibration and recurrent adaptation: Towards a plug and play online ERD-BCI. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 20(3), 313-319. https://doi.org/10.1109/tnsre.2012.2189584\n\nNotes\n\n.. note::\n\n``BNCI2015_001`` was previously named ``BNCI2015001``. ``BNCI2015001`` will be removed in version 1.1.\n\n.. versionadded:: 0.4.0\nAppelhoff, S., Sanderson, M., Brooks, T., Vliet, M., Quentin, R., Holdgraf, C., Chaumon, M., Mikulan, E., Tavabi, K., Hochenberger, R., Welke, D., Brunner, C., Rockhill, A., Larson, E., Gramfort, A. and Jas, M. (2019). MNE-BIDS: Organizing electrophysiological data into the BIDS format and facilitating their analysis. Journal of Open Source Software 4: (1896). https://doi.org/10.21105/joss.01896\n\nPernet, C. R., Appelhoff, S., Gorgolewski, K. J., Flandin, G., Phillips, C., Delorme, A., Oostenveld, R. (2019). EEG-BIDS, an extension to the brain imaging data structure for electroencephalography. Scientific Data, 6, 103. https://doi.org/10.1038/s41597-019-0104-8\n\n---\nGenerated by MOABB 1.4.3 (Mother of All BCI Benchmarks)\nhttps://github.com/NeuroTechX/moabb\n","bids_version":"1.9.0","sessions_count":3,"publish_date":"2026-04-17 13:58:04","embedding_dirty":0,"license_tier":"noderiv","zarr_status":"ready","zarr_converted_at":"2026-09-04 12:56:20","zarr_store_count":28,"zarr_index_etag":"4350f5d615b9aac841274f79984e96cf","zarr_source_commit":"18fdfe82823b6ad6be09ffb46e3dc1c879ae6263","archive_status":"ready","archive_size":2901238899,"archive_retry_count":0,"records_status":"ready","archive_skip_reason":null,"zarr_errors":0,"zarr_failure_count":0,"zarr_deterministic":0,"zarr_failed_at":null,"num_dataset_citations":0,"num_datapaper_citations":95,"n_channels":13,"electrode_system":"10-10","has_hed":1,"hed_version":"8.4.0","is_exemplar":0,"bytes_present":3042203782,"data_complete":1,"withdrawn_at":null,"withdrawn_reason":null,"archive_complete":1,"archive_absent_files":0,"archive_declared_files":349,"zarr_pool_breaks":0,"total_recording_duration":60102,"recording_duration_min":2142,"recording_duration_max":2160,"recording_count":28,"recordings_unavailable":0,"recordings_measured":28,"channel_count_min":13,"channel_count_max":13,"sampling_frequency":512,"power_line_frequency":50,"eeg_reference":"Car","placement_scheme":"10-20 system","sweep_stamps":"{\"enrichment_updated_at\":\"2026-08-18 18:10:03\",\"metadata_updated_at\":\"2026-08-18 18:11:03\",\"archive_checked_at\":\"2026-08-18 18:17:33\",\"zarr_checked_at\":\"2026-06-07 17:58:21\",\"records_checked_at\":\"2026-08-18 18:14:49\",\"citations_updated_at\":\"2026-09-08 03:00:46\",\"channel_montage_checked_at\":\"2026-06-28 22:52:03\",\"hed_checked_at\":\"2026-06-30 04:11:24\",\"data_checked_at\":null,\"availability_report_at\":\"2026-08-19 03:00:52\",\"signal_defaults_at\":\"2026-09-02 11:38:23\",\"recording_stats_at\":\"2026-09-05 03:00:38\",\"zarr_verify_attempted_at\":\"2026-09-07 03:02:11\",\"zarr_verified_at\":\"2026-09-07 03:02:11\",\"zarr_verified_commit\":\"18fdfe82823b6ad6be09ffb46e3dc1c879ae6263\",\"zarr_verify_status\":\"verified\",\"zarr_verify_examples\":[],\"zarr_verify_sampled\":28.0,\"zarr_verify_checked\":28.0,\"zarr_verify_checked_channels\":28.0,\"zarr_verify_checked_duration\":28.0,\"zarr_verify_checked_rate\":28.0,\"zarr_verify_unchecked\":0.0,\"zarr_verify_mismatch_count\":0.0,\"zarr_verify_examples_truncated\":0.0}","participants":12,"num_citations":95,"latest_version":"v1.0.2","zarr_verify_status":"verified","zarr_verified_at":"2026-09-07 03:02:11","owner_username":"bruaristimunha","owner_github":"bruAristimunha","file_size_formatted":"2.83 GB","zarr_data_failures":null,"zarr_index_url":"https://zarr.nemar.org/nm000140/zarr/index.json","attestation_deposit_type":null,"attestation_key_status":null,"attestation_deidentified":null,"attestation_no_duplicate":null,"attestation_upstream_source":null,"attestation_accepted_at":null}}