{"dataset":{"id":"47569","dataset_id":"nm000258","name":"Imagined Speech EEG database — Spanish vowels and commands (Pressel et al. 2016)","description":"An open-access EEG dataset containing recordings from 15 healthy Spanish-speaking subjects performing imagined speech tasks. The dataset comprises 11 imagery classes (5 Spanish vowels and 6 directional commands) acquired using 6-channel EEG at 1024 Hz with preprocessed data (bandpass filtered 2-45 Hz). This BIDS-reformatted derivative is based on the original data described in Pressel et al. 2016 and supports brain-computer interface research and motor imagery classification studies.","owner_user_id":19,"status":"active","github_repo":"nemarDatasets/nm000258","concept_doi":"10.82901/nemar.nm000258","latest_version_doi":"10.82901/nemar.nm000258.v1.0.4","created_at":"2026-06-19 23:12:16","updated_at":"2026-08-18 18:18:51","zenodo_concept_id":null,"is_sandbox":0,"visibility":"public","ezid_status":"public","enrichment_json":"{\n  \"version\": \"2.0\",\n  \"pipeline_stage\": \"validated\",\n  \"title\": \"Imagined Speech EEG database — Spanish vowels and commands (Pressel et al. 2016)\",\n  \"description\": \"An open-access EEG dataset containing recordings from 15 healthy Spanish-speaking subjects performing imagined speech tasks. The dataset comprises 11 imagery classes (5 Spanish vowels and 6 directional commands) acquired using 6-channel EEG at 1024 Hz with preprocessed data (bandpass filtered 2-45 Hz). This BIDS-reformatted derivative is based on the original data described in Pressel et al. 2016 and supports brain-computer interface research and motor imagery classification studies.\",\n  \"methods_description\": \"EEG signals were recorded from 15 healthy subjects (age 24-28 years) using a Grass 8-18-36 amplifier with DataTranslation DT9816 ADC. Six channels (F3, F4, C3, C4, P3, P4) were positioned according to the standard 10-20 montage at a sampling rate of 1024 Hz with online bandpass filtering (2-45 Hz). Subjects performed cue-based imagery tasks of 5 Spanish vowels and 6 directional commands in response to visual stimuli, with trial duration of 4 seconds and imagery period of 3 seconds. Data were preprocessed with bandpass filtering and artifact rejection applied.\",\n  \"license\": \"other-open\",\n  \"dataset_type\": \"derivative\",\n  \"authors\": {\n    \"German A. Pressel Coretto\": {},\n    \"Ivan E. Gareis\": {},\n    \"Hugo Leonardo Rufiner\": {}\n  },\n  \"keywords\": [\n    {\n      \"term\": \"imagined speech\"\n    },\n    {\n      \"term\": \"EEG\"\n    },\n    {\n      \"term\": \"motor imagery\"\n    },\n    {\n      \"term\": \"Brain-Computer Interfaces\",\n      \"subject_scheme\": \"MeSH\",\n      \"value_uri\": \"http://id.nlm.nih.gov/mesh/D062207\"\n    },\n    {\n      \"term\": \"Spanish vowels\"\n    },\n    {\n      \"term\": \"directional commands\"\n    },\n    {\n      \"term\": \"BIDS\"\n    },\n    {\n      \"term\": \"open access database\"\n    },\n    {\n      \"term\": \"preprocessing\"\n    }\n  ],\n  \"related_identifiers\": [\n    {\n      \"identifier\": \"10.1117/12.2255697\",\n      \"identifier_type\": \"DOI\",\n      \"relation_type\": \"IsDerivedFrom\"\n    },\n    {\n      \"identifier\": \"https://github.com/nemarDatasets/nm000258\",\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/nm000258\",\n      \"identifier_type\": \"URL\",\n      \"relation_type\": \"IsDescribedBy\"\n    }\n  ],\n  \"resource_type_general\": \"Dataset\",\n  \"resource_type_specific\": \"EEG Dataset\",\n  \"modalities\": [\n    \"eeg\"\n  ],\n  \"sizes\": [\n    \"2.2 GB (31 files)\"\n  ],\n  \"formats\": [\n    \".edf\",\n    \".json\",\n    \".mat\",\n    \".md\",\n    \".tsv\",\n    \".yaml\",\n    \".yml\"\n  ],\n  \"source_hash\": \"a42ee664e0a4a5e5b7017263e0731bcfb6140a568fa8feecb25f7e9b9ca7d412\"\n}","last_activity_at":"2026-08-16 13:36:20","source":null,"source_id":null,"subject_count":15,"modalities":"eeg","age_min":null,"age_max":null,"file_size":2151095085,"total_files":191,"tasks":"imagery","metadata_columns_error":null,"staleness_warn_stage":null,"staleness_admin_notified_at":null,"authors":"German A. Pressel Coretto, Ivan E. Gareis, Hugo Leonardo Rufiner","license":"other-open","readme":"[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.nm000258-blue)](https://doi.org/10.82901/nemar.nm000258)\n\n# Imagined Speech EEG database — Spanish vowels and commands (Pressel et al. 2016)\n\n## Overview\n\nAn open-access EEG dataset comprising recordings from 15 healthy Spanish-speaking subjects during imagined speech tasks. The dataset includes 11 imagery classes: 5 Spanish vowels and 6 directional commands, acquired using 6-channel EEG at 1024 Hz with preprocessed data (bandpass filtered 2-45 Hz). Trials consist of 4-second periods with a 3-second imagery window occurring within each trial. This resource supports brain-computer interface research and motor imagery classification studies.\n\n## Dataset Summary\n\n| Property | Value |\n|---|---|\n| Subjects | 15 |\n| Channels | 6 |\n| Classes | 11 |\n| Trial length | 4 s |\n| Sampling frequency | 1024 Hz |\n| Sessions | 1 |\n| Total trials | 8670 |\n| Paradigm | MotorImagery |\n\n## Data Collection Methods\n\nEEG signals were recorded from 15 healthy subjects (age 24-28 years) using a Grass 8-18-36 amplifier with DataTranslation DT9816 ADC. Six channels (F3, F4, C3, C4, P3, P4) were positioned according to the standard 10-20 montage. Sampling rate was 1024 Hz with online bandpass filtering (2-45 Hz). Subjects performed cue-based imagery tasks of 5 Spanish vowels and 6 directional commands in response to visual stimuli, with trial duration of 4 seconds and imagery period of 3 seconds. Data were preprocessed with bandpass filtering and artifact rejection applied.\n\n## How to Access via MOABB\n\nInstall MOABB and load this dataset directly:\n\n```python\nfrom moabb.datasets import Pressel2016\nfrom moabb.paradigms import MotorImagery\nparadigm = MotorImagery()\n\ndataset = Pressel2016()\nX, y, metadata = paradigm.get_data(dataset)\n```\n\nFor more details see the [MOABB documentation](https://moabb.neurotechx.com/) and the\n[MOABB dataset page](https://moabb.neurotechx.com/docs/generated/moabb.datasets.Pressel2016.html).\n\n## Citation\n\nIf you use this dataset please cite the primary publication:\n\n> DOI: [10.1117/12.2255697](https://doi.org/10.1117/12.2255697)\n\n## NEMAR / MOABB Benchmark Collection\n\nThis BIDS-formatted dataset was converted from the original data using the\n[MOABB](https://moabb.neurotechx.com/) pipeline and re-hosted on\n[NEMAR](https://nemar.org/) as part of the MOABB benchmark collection.\nThe original data and license terms apply — see `dataset_description.json` for details.\n","bids_version":"1.9.0","sessions_count":1,"publish_date":null,"embedding_dirty":0,"license_tier":"unknown","zarr_status":"ready","zarr_converted_at":"2026-08-22 07:38:50","zarr_store_count":15,"zarr_index_etag":"c180a6f8b929c60f1b615dcd30fa9c5d","zarr_source_commit":"966af11dcff0121aa01ab1e951a786e570c3d6b2","archive_status":"ready","archive_size":2097563616,"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":92,"n_channels":6,"electrode_system":"10-20","has_hed":1,"hed_version":"8.4.0","is_exemplar":0,"bytes_present":2150725378,"data_complete":1,"withdrawn_at":null,"withdrawn_reason":null,"archive_complete":1,"archive_absent_files":0,"archive_declared_files":191,"zarr_pool_breaks":null,"total_recording_duration":30789,"recording_duration_min":1896,"recording_duration_max":2424,"recording_count":15,"recordings_unavailable":0,"recordings_measured":15,"channel_count_min":6,"channel_count_max":6,"sampling_frequency":1024,"power_line_frequency":50,"eeg_reference":null,"placement_scheme":"10-20 system","sweep_stamps":"{\"enrichment_updated_at\":\"2026-08-18 18:15:45\",\"metadata_updated_at\":\"2026-08-18 18:18:49\",\"archive_checked_at\":\"2026-08-18 18:24:40\",\"zarr_checked_at\":null,\"records_checked_at\":\"2026-08-18 18:20:50\",\"citations_updated_at\":\"2026-09-08 03:00:46\",\"channel_montage_checked_at\":\"2026-06-28 23:01:19\",\"hed_checked_at\":\"2026-06-30 04:31:30\",\"data_checked_at\":null,\"availability_report_at\":\"2026-08-22 03:01:08\",\"recording_stats_at\":\"2026-09-02 11:32:04\",\"signal_defaults_at\":\"2026-09-02 11:49:30\"}","participants":15,"num_citations":92,"latest_version":"v1.0.4","zarr_verify_status":null,"zarr_verified_at":null,"owner_username":"bruaristimunha","owner_github":"bruAristimunha","file_size_formatted":"2.00 GB","zarr_data_failures":null,"zarr_index_url":"https://zarr.nemar.org/nm000258/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}}