NY Metadata (YAML)

This document describes the standard dictionary structure used in .yml metadata files for EEG time series data in the NY format.

Overview

The YAML format has been employed for easily sharing EEG metadata in Python and Julia environments. Each .yml file provides comprehensive metadata for its corresponding .npz data file.

Dictionary Structure

The YAML file contains four main dictionaries:

acquisition

Contains all technical information about the EEG data acquisition process.

FieldTypeDescriptionExample
filterStringFilter settings of the EEG acquisition machine"Low-Pass 83Hz (Butterworth order 4 zero phase) for downsampling"
groundStringLocation of the ground electrode"Fpz" or "N/A"
referenceStringLocation of the reference electrode"A1" or "N/A"
hardwareStringCommercial name and producer of EEG amplifier"g.tec EEG - g.USBamp EEG amplifier"
softwareStringSoftware used for data acquisition"OpenViBE, INRIA (France)" or "N/A"
samplingrateIntegerSampling rate in Hz256
sensorsArray of StringsEEG electrode locations (excluding ground/reference)["Fpz", "F7", "F3", "Fz", ...]
sensortypeStringType and material of electrodes"Ag/AgCl Wet electrodes"

documentation

Contains references and documentation links for the dataset.

FieldTypeDescriptionExample
descriptionStringLink to dataset description"https://zenodo.org/records/806023"
doiStringDigital Object Identifier"https://theses.hal.science/tel-01196752"
investigatorsStringPrincipal investigators"Alexandre Barachant"
placeStringInstitution where experiment was conducted"GIPSA-lab..."
repositoryStringLink to data repository"https://zenodo.org/records/806023"

id

Contains identification information for the specific recording.

FieldTypeDescriptionExample
conditionStringExperimental condition"None" or specific condition
databaseStringName of the database"AlexMI"
paradigmStringBCI paradigm type"MI" or "P300"
runIntegerRun number within session1
sessionIntegerSession number1
subjectIntegerSubject identifier1
timestampIntegerYear of data collection2012

stim

Contains stimulation and labeling information.

FieldTypeDescriptionExample
labelsDictionaryMapping of class names to numeric codes{"right_hand": 2, "feet": 3, "rest": 4}
nclassesIntegerTotal number of stimulus classes3
trials_per_classDictionaryNumber of trials available for each class{"feet": 20, "rest": 20, "right_hand": 20}
offsetIntegerOffset in samples from stimulation to trial start0
windowlengthIntegerTrial duration in samples768

Example Structure

formatversion: 0.0.1

acquisition:
  filter: "Low-Pass 83Hz (Butterworth order 4 zero phase) for downsampling"
  ground: "N/A"
  hardware: "g.tec EEG - g.USBamp EEG amplifier"
  reference: "N/A"
  samplingrate: 256
  sensors: ["Fpz", "F7", "F3", "Fz", "F4", "F8", "T7", "C3", "Cz", "C4", "T8", "P7", "P3", "Pz", "P4", "P8"]
  sensortype: "Ag/AgCl Wet electrodes"
  software: "N/A"

documentation:
  description: "https://zenodo.org/records/806023"
  doi: "https://theses.hal.science/tel-01196752"
  investigators: "Alexandre Barachant"
  place: "Laboratoire Electronique et systeme pour la sante CEA-LETI dans l'Ecole Doctorale : EEATS, Universite de Grenoble"
  repository: "https://zenodo.org/records/806023"

id:
  condition: "None"
  database: "AlexMI"
  paradigm: "MI"
  run: 1
  session: 1
  subject: 1
  timestamp: 2012

stim:
  labels:
    right_hand: 2
    feet: 3
    rest: 4
  nclasses: 3
  trials_per_class:
    right_hand: 20
    feet: 20
    rest: 20
  offset: 0
  windowlength: 768