{"dataset":{"id":"61256","dataset_id":"on007788","name":"Dataset: EEG-Controlled Exoskeleton for Walking and Standing - A Longitudinal Study of Healthy Individuals","description":"This dataset contains multimodal brain–machine interface (BMI) recordings from seven healthy adults who trained over nine longitudinal sessions to control a lower-limb exoskeleton via motor imagery. It includes 60-channel EEG, 4-channel EOG, dual IMU motion data, and exoskeleton control/feedback signals collected during open-loop calibration and closed-loop walk/stop trials. The dataset supports research on EEG-based decoding of motor imagery for neurorehabilitation and human-robot interaction applications.","owner_user_id":15,"status":"active","github_repo":"nemarDatasets/on007788","concept_doi":"10.82901/nemar.on007788","latest_version_doi":"10.82901/nemar.on007788.v1.0.0","created_at":"2026-06-30 20:01:50","updated_at":"2026-08-18 23:31:22","zenodo_concept_id":null,"is_sandbox":0,"visibility":"public","ezid_status":"public","enrichment_json":"{\n  \"version\": \"2.0\",\n  \"pipeline_stage\": \"validated\",\n  \"title\": \"Dataset: EEG-Controlled Exoskeleton for Walking and Standing - A Longitudinal Study of Healthy Individuals\",\n  \"description\": \"This dataset contains multimodal brain–machine interface (BMI) recordings from seven healthy adults who trained over nine longitudinal sessions to control a lower-limb exoskeleton via motor imagery. It includes 60-channel EEG, 4-channel EOG, dual IMU motion data, and exoskeleton control/feedback signals collected during open-loop calibration and closed-loop walk/stop trials. The dataset supports research on EEG-based decoding of motor imagery for neurorehabilitation and human-robot interaction applications.\",\n  \"methods_description\": \"Seven healthy adults (ages 20-30) completed nine sessions each, comprising a motor imagery calibration phase (training) without feedback and a closed-loop trial phase with 12 trials per session, followed by extended 6-minute walk and stop motor imagery tasks. Recordings included 60-channel scalp EEG plus 4 EOG channels, IMU sensors (accelerometer, gyroscope, magnetometer, quaternion) mounted on the forehead and exoskeleton back brace, and logged exoskeleton control/feedback signals. Data are provided raw, without filtering or artifact removal.\",\n  \"license\": \"CC0\",\n  \"dataset_type\": \"raw\",\n  \"authors\": {\n    \"Shantanu Sarkar\": {},\n    \"Kevin Nathan\": {},\n    \"Jose L. Contreras-Vidal\": {}\n  },\n  \"keywords\": [\n    {\n      \"term\": \"EEG\"\n    },\n    {\n      \"term\": \"brain-computer interface\"\n    },\n    {\n      \"term\": \"motor imagery\"\n    },\n    {\n      \"term\": \"exoskeleton\"\n    },\n    {\n      \"term\": \"Electrooculography\",\n      \"subject_scheme\": \"MeSH\",\n      \"value_uri\": \"http://id.nlm.nih.gov/mesh/D004585\"\n    },\n    {\n      \"term\": \"longitudinal study\"\n    },\n    {\n      \"term\": \"gait\"\n    }\n  ],\n  \"related_identifiers\": [\n    {\n      \"identifier\": \"https://github.com/nemarDatasets/on007788\",\n      \"identifier_type\": \"URL\",\n      \"relation_type\": \"IsDescribedBy\"\n    },\n    {\n      \"identifier\": \"https://nemar.org/dataset/on007788\",\n      \"identifier_type\": \"URL\",\n      \"relation_type\": \"IsDescribedBy\"\n    },\n    {\n      \"identifier\": \"10.18112/openneuro.ds007788\",\n      \"identifier_type\": \"DOI\",\n      \"relation_type\": \"IsVersionOf\"\n    },\n    {\n      \"identifier\": \"10.18112/openneuro.ds007788.v1.0.1\",\n      \"identifier_type\": \"DOI\",\n      \"relation_type\": \"IsDerivedFrom\"\n    }\n  ],\n  \"funding_references\": [\n    {\n      \"funder_name\": \"UH–Methodist Graduate Fellowship for Translational Research\"\n    },\n    {\n      \"funder_name\": \"NSF\",\n      \"award_number\": \"2137255\",\n      \"award_title\": \"IUCRC BRAIN Center\"\n    }\n  ],\n  \"resource_type_general\": \"Dataset\",\n  \"resource_type_specific\": \"EEG Dataset\",\n  \"modalities\": [\n    \"eeg\",\n    \"motion\"\n  ],\n  \"sizes\": [\n    \"3.2 GB (3285 files)\"\n  ],\n  \"formats\": [\n    \".edf\",\n    \".gz\",\n    \".json\",\n    \".md\",\n    \".pdf\",\n    \".tsv\",\n    \".xls\",\n    \".yml\"\n  ],\n  \"source_hash\": \"299c81224ace23dbc90588560a5d0d9cc6d9408b6425c112677905b9de618c38\"\n}","last_activity_at":"2026-06-30 20:01:50","source":"openneuro","source_id":"ds007788","subject_count":7,"modalities":"eeg,motion","age_min":null,"age_max":null,"file_size":3884594010,"total_files":17283,"tasks":"stop6min,training,trial01,trial02,trial03,trial04,trial05,trial06,trial07,trial08,trial09,trial10,trial11,trial12,walk6min","metadata_columns_error":null,"staleness_warn_stage":null,"staleness_admin_notified_at":null,"authors":"Shantanu Sarkar, Kevin Nathan, Jose L. Contreras-Vidal","license":"CC0","readme":"[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on007788-blue)](https://doi.org/10.82901/nemar.on007788)\n\n## **EEG-Controlled Exoskeleton for Walking and Standing – A Longitudinal Motor Imagery Study in Healthy Adults**\n\n### **Dataset Overview**\nThis dataset comprises multimodal recordings from a brain–machine interface (BMI) training study involving seven healthy adult participants (ages 20–30 years; mean = 24.3, SD = 3.8). The study investigated both open-loop and closed-loop control of a lower-limb exoskeleton (Rex Bionics). The dataset includes 60-channel EEG, 4-channel EOG, motion data from two IMU sensors (mounted on the participant's forehead and the exoskeleton), and exoskeleton control and feedback signals. Each participant completed nine sessions over several weeks, with each session structured into a training phase followed by a closed-loop trial phase.\n\n### **Experimental Design**\n\n- **Participants:** 7 healthy adults (4 male, 3 female)\n- **Sessions:** 9 per participant\n- **Training Phase:** Motor imagery calibration\n- **Trial Phase:** Closed-loop BMI control (walk/stop)\n- **Conditions:** Walk / Stop (motor imagery)\n\n### **Task Structure**\n\n**Training:**\nParticipants perform motor imagery tasks without feedback to calibrate the BMI decoder.\n\n**TrialXX:**\nEach session includes 12 closed-loop BMI trials (trial01–trial12), during which participants use motor imagery to control the exoskeleton in real time.\n\n- **Block 1:** Trials 1–4\n- **Block 2:** Trials 5–8\n- **Block 3:** Trials 9–12\n\n**walk6min / stop6min:**\nAfter the 12 trials, participants complete two extended motor imagery tasks:\n\n- **walk6min:** Imagining continuous walking for 6 minutes\n- **stop6min:** Imagining standing still for 6 minutes\n\n### **Data Modalities**\n\n- **EEG:** 60 scalp channels + 4 EOG channels\n- **IMU:** 3-axis accelerometer, gyroscope, magnetometer, and quaternion\n- **Sensor Placement:** IMUs mounted on the participant's forehead and the exosuit back brace\n- **Decoder Signals / Feedback:** Logged control signals and BMI predictions\n\n### **Additional Materials**\n\n- **MIQ‑RS:** Motor Imagery Questionnaire – Revised Second Version (PDFs in `derivatives/MIQ-RS/`)\n- **Validation Tables:** Data availability, synchronization, and electrode placement (`derivatives/validation/`)\n- **Raw Data:** Provided without filtering or artifact removal\n\n### **Folder Structure**\n\n---\n\n```\ndataset-root/\n│\n├── sub-{SubNo}/\n│   └── ses-{SesNo}/\n│       ├── eeg/\n│       │   ├── sub-{SubNo}_ses-{SesNo}_coordsystem.json\n│       │   ├── sub-{SubNo}_ses-{SesNo}_electrodes.tsv\n│       │   ├── sub-{SubNo}_ses-{SesNo}_electrodes.json\n│       │   │\n│       │   ├── sub-{SubNo}_ses-{SesNo}_task-{Task}_eeg.edf\n│       │   ├── sub-{SubNo}_ses-{SesNo}_task-{Task}_eeg.json\n│       │   │\n│       │   ├── sub-{SubNo}_ses-{SesNo}_task-{Task}_acq-{AcqLabel}_events.tsv\n│       │   ├── sub-{SubNo}_ses-{SesNo}_task-{Task}_acq-{AcqLabel}_events.json\n│       │   │\n│       │   ├── sub-{SubNo}_ses-{SesNo}_task-{Task}_recording-{StimLabel}_stim.tsv.gz\n│       │   └── sub-{SubNo}_ses-{SesNo}_task-{Task}_recording-{StimLabel}_stim.json\n│       │\n│       └── motion/\n│           ├── sub-{SubNo}_ses-{SesNo}_task-{Task}_tracksys-{IMUPos}_motion.tsv\n│           ├── sub-{SubNo}_ses-{SesNo}_task-{Task}_tracksys-{IMUPos}_motion.json\n│           ├── sub-{SubNo}_ses-{SesNo}_task-{Task}_tracksys-{IMUPos}_channels.tsv\n│           └── sub-{SubNo}_ses-{SesNo}_task-{Task}_tracksys-{IMUPos}_channels.json\n│\n└── derivatives/\n    ├── MIQ-RS/\n    │   └── sub-{SubNo}_MIQ-RS.pdf\n    │\n    └── validation/\n        ├── BeepValidation.xls\n        ├── ExoIMU_Stats.xls\n        ├── ExoIMU_W_vs_S.xls\n        ├── HeadIMU_Stats.xls\n        ├── HeadIMU_W_vs_S.xls\n        ├── IMU_Orientation.xls\n        ├── Training-OpenLoop-Stats.xls\n        ├── Trial-CloseLoop-Stats.xls\n        ├── failCounterValidation.xls\n        ├── infoClosedLoopValidation.xls\n        ├── rexCommandValidation.xls\n        └── rexStateValidation.xls\n```\n\n### **Naming Convention**\n\n| Placeholder | Description | Values |\n|---|---|---|\n| `{SubNo}` | Participant ID | 01–07 |\n| `{SesNo}` | Session Number | 01–09 |\n| `{Task}` | Task name | `training`, `trial01–trial12`, `stop6min`, `walk6min` |\n| `{AcqLabel}` | Acquisition label | `infoclosedloop`, `rexcommand`, `rexstate` |\n| `{StimLabel}` | Stimulus label | `beep`, `failcounter` |\n| `{IMUPos}` | IMU position | `head`, `exo` |\n\n### **Citation**\nIf you use this dataset, please cite the associated study and acknowledge the contributors.\n","bids_version":"1.8.0","sessions_count":9,"publish_date":null,"embedding_dirty":0,"license_tier":"public","zarr_status":"ready","zarr_converted_at":"2026-08-22 23:55:44","zarr_store_count":935,"zarr_index_etag":"74e2bb717574a9a303b3c3c7d7cc7b78","zarr_source_commit":"1e2649fe8051b1f28fbf11c7c38414765ce38ca7","archive_status":"ready","archive_size":2284033522,"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":2,"num_datapaper_citations":0,"n_channels":60,"electrode_system":null,"has_hed":0,"hed_version":null,"is_exemplar":0,"bytes_present":3195950218,"data_complete":1,"withdrawn_at":null,"withdrawn_reason":null,"archive_complete":null,"archive_absent_files":null,"archive_declared_files":null,"zarr_pool_breaks":null,"total_recording_duration":122479.86000000004,"recording_duration_min":45.63,"recording_duration_max":375.18,"recording_count":935,"recordings_unavailable":0,"recordings_measured":935,"channel_count_min":64,"channel_count_max":64,"sampling_frequency":100,"power_line_frequency":60,"eeg_reference":"Ref","placement_scheme":"10-20","sweep_stamps":"{\"enrichment_updated_at\":\"2026-08-18 23:31:02\",\"metadata_updated_at\":\"2026-08-18 23:31:20\",\"archive_checked_at\":\"2026-06-30 20:26:12\",\"zarr_checked_at\":null,\"records_checked_at\":\"2026-06-30 20:17:42\",\"citations_updated_at\":\"2026-09-08 03:00:52\",\"channel_montage_checked_at\":null,\"hed_checked_at\":null,\"data_checked_at\":\"2026-09-05 03:00:21\",\"availability_report_at\":\"2026-07-23 01:33:46\",\"recording_stats_at\":\"2026-09-02 11:34:07\",\"signal_defaults_at\":\"2026-09-02 12:58:26\"}","participants":7,"num_citations":2,"latest_version":"v1.0.0","zarr_verify_status":null,"zarr_verified_at":null,"owner_username":"nemarAdmin","owner_github":"nemarAdmin","file_size_formatted":"3.62 GB","zarr_data_failures":null,"zarr_index_url":"https://zarr.nemar.org/on007788/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}}