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feat: add multimodal example
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‎emg_multimodal/README.md‎

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# EMG Multimodal Dataset
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## Overview
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This is a simplified example dataset derived from OpenNeuro ds003739 demonstrating the integration of EEG, EMG, and motion capture data in BIDS format. The dataset contains simultaneous recordings from all three modalities during a perturbed balance task.
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## Modalities
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- **EEG**: 128-channel electroencephalography using a Biosemi ActiveTwo system
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- **EMG**: 10-channel electromyography from neck and lower leg muscles
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- **Motion Capture**: 3D position tracking of head and sacrum markers
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- **EOG**: 3-channel electrooculography
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## Task Description
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Participants stood on a treadmill-mounted balance beam (2.5 cm tall, 12.7 cm wide) and were exposed to sensorimotor perturbations consisting of side-to-side waist pulls lasting 1 second. Each session involved 150 perturbation events balanced between pull directions.
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## Data Acquisition
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All data were recorded synchronously at 256 Hz using a Biosemi ActiveTwo system. The recording includes:
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- 128 EEG channels with common median reference
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- 10 EMG channels (neck and lower leg muscles)
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- 3 EOG channels
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- Motion capture data for sacrum and head positions
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- Load cell data from left and right sides
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## Reference
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This example is based on the study:
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Peterson SM & Ferris DP (2018). Differentiation in theta and beta electrocortical activity between visual and physical perturbations to walking and standing balance. eNeuro, 5(4): ENEURO.0207-18.2018.
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Full dataset: https://openneuro.org/datasets/ds003739

‎emg_multimodal/dataset_description.json‎

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{
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"Name": "EMG multimodal",
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"BIDSVersion": "1.10.0",
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"DatasetType": "raw",
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"License": "CC0",
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"Authors": [
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"Steven Peterson",
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"Daniel Ferris"
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],
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"Acknowledgements": "This is a simplified example dataset derived from OpenNeuro ds003739 to demonstrate BIDS formatting for multimodal EEG-EMG-Motion data.",
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"HowToAcknowledge": "Please cite the original study: Peterson SM & Ferris DP (2018). Differentiation in theta and beta electrocortical activity between visual and physical perturbations to walking and standing balance. eNeuro, 5(4): ENEURO.0207-18.2018.",
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"ReferencesAndLinks": [
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"https://doi.org/10.1523/ENEURO.0207-18.2018",
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"https://doi.org/10.1016/j.neuroimage.2019.05.038"
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],
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"SourceDatasets": [
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{
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"DOI": "10.18112/openneuro.ds003739.v1.0.2",
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"URL": "https://openneuro.org/datasets/ds003739",
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"Version": "1.0.2"
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}
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]
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}

‎emg_multimodal/participants.json‎

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{
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"age": {
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"Description": "Age of the participant",
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"Units": "years"
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},
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"sex": {
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"Description": "Biological sex of the participant",
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"Levels": {
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"M": "male",
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"F": "female"
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}
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},
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"handedness": {
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"Description": "Handedness of the participant",
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"Levels": {
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"left": "left-handed",
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"right": "right-handed",
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"ambidextrous": "ambidextrous"
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}
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}
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}

‎emg_multimodal/participants.tsv‎

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participant_id age sex handedness
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sub-01 28 F right

‎emg_multimodal/scans.json‎

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{
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"acq_time": {
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"Description": "Acquisition time of the scan",
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"Units": "ISO 8601 datetime"
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}
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}

‎emg_multimodal/sub-01/eeg/sub-01_coordsystem.json‎

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{"EEGCoordinateUnits":"mm","EEGCoordinateSystem":"CTF","EEGCoordinateSystemDescription":"EEGLAB"}

‎emg_multimodal/sub-01/eeg/sub-01_electrodes.tsv‎

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L_vertical_eog 0.09 0.03 0.03
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L_leg_emg_tibialis_anterior n/a n/a n/a
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L_leg_emg_soleus n/a n/a n/a
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L_leg_emg_medial_gastrocnemius n/a n/a n/a
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L_leg_emg_peroneus_longus n/a n/a n/a
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R_leg_emg_tibialis_anterior n/a n/a n/a
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Mocap_sacrum_mediolateral n/a n/a n/a
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Mocap_sacrum_anteriorposterior n/a n/a n/a
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Mocap_head_mediolateral n/a n/a n/a
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Mocap_head_anteriorposterior n/a n/a n/a
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L_load_cell n/a n/a n/a
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R_load_cell n/a n/a n/a

‎emg_multimodal/sub-01/eeg/sub-01_task-pullstand_channels.tsv‎

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name type units
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A1 EEG microV
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A2 EEG microV
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A3 EEG microV
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A4 EEG microV
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A5 EEG microV
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A6 EEG microV
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A7 EEG microV
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A8 EEG microV
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A9 EEG microV
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A10 EEG microV
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A11 EEG microV
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A12 EEG microV
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A13 EEG microV
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A14 EEG microV
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A15 EEG microV
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A17 EEG microV
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A18 EEG microV
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A19 EEG microV
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A20 EEG microV
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A21 EEG microV
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A22 EEG microV
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A23 EEG microV
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A24 EEG microV
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A25 EEG microV
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A26 EEG microV
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A27 EEG microV
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A28 EEG microV
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A29 EEG microV
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A30 EEG microV
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A31 EEG microV
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A32 EEG microV
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B1 EEG microV
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B2 EEG microV
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B3 EEG microV
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B4 EEG microV
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B5 EEG microV
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B6 EEG microV
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B7 EEG microV
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B8 EEG microV
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B9 EEG microV
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B10 EEG microV
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B19 EEG microV
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B20 EEG microV
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B21 EEG microV
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B23 EEG microV
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B24 EEG microV
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B25 EEG microV
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B26 EEG microV
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B27 EEG microV
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B28 EEG microV
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B29 EEG microV
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B30 EEG microV
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B31 EEG microV
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B32 EEG microV
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C1 EEG microV
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C2 EEG microV
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C3 EEG microV
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C4 EEG microV
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C5 EEG microV
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C6 EEG microV
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C10 EEG microV
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C15 EEG microV
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C16 EEG microV
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C17 EEG microV
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C18 EEG microV
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C20 EEG microV
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C21 EEG microV
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C22 EEG microV
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C23 EEG microV
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C24 EEG microV
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C25 EEG microV
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C26 EEG microV
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C27 EEG microV
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C28 EEG microV
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C29 EEG microV
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C30 EEG microV
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C31 EEG microV
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C32 EEG microV
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D1 EEG microV
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D2 EEG microV
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D3 EEG microV
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D4 EEG microV
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D5 EEG microV
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D32 EEG microV
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R_horizontal_eog EOG microV
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L_horizontal_eog EOG microV
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L_vertical_eog EOG microV

‎emg_multimodal/sub-01/eeg/sub-01_task-pullstand_eeg.edf‎

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