A dataset of EOG recordings during a BCI task with a participant with ALS

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README.md

ALS_EOG

A dataset of EEG and EOG recordings during a BCI task with a participant with ALS.

A substantial part of these data have been already published in Jaramillo-Gonzalez, Wu, Tonin, et al. (2021).

At the time of the first recording the patient was artificially fed, artificially ventilated and already in Locked-In State since he was not able to use eye-tracker-based AAC devices anymore.

Recordings have been performed at the patient's house during 13 visits. Each visit consists of one or more consecutive days during which BCI sessions have been conducted. Data belonging to the same visit are stored in the same subfolder.

For more information about the recordings, please refer to Tonin, Jaramillo-Gonzalez, et al. (2020) and Jaramillo-Gonzalez, Wu, Tonin, et al. (2021).

BCI Paradigm

During the BCI session the participant had to reply to known yes/no questions by moving the eyes in two different ways.

Each session consists of blocks of usually 20 trials. Each trial is formed by:

  1. Baseline: the participant was asked to relax (~3-10s)
  2. Stimulus: a known yes/no question was auditorily presented (~5s)
  3. Response: The participant performed the eye movement (~3-10s)
  4. Feedback: The classification of the response signal was auditorily presented (~2-3s)

Data

Data have been acquired with a 16 channel EEG amplifier (V-Amp DC, Brain Products, Germany) with Ag/AgCl active electrodes.

Data have been acquired at 500Hz, and are stored in the raw format directly provided by Brain Product software.

Each session consists in 3 files:

  • Header file (*.vhdr), containing recording parameters and further meta-information, as the scaling factor necessary to convert the recorded raw amplitude to milivolts.
  • Marker file (*.vmrk) describes the events and their onset during the data recording, in this case, the sequence of triggers.
  • Raw EEG data file (*.eeg) is a binary file containing the EEG and EOG data and additional recorded signals.

Channel names use standard EEG 10-20 names, except for the following names:

Channel 10-20
L1 F3
L2 AF3
R1 F4
R2 AF4
EOGU SO1
EOGD IO1
EOGL LO1
EOGR LO2

Markers

Markers have been sent throw serial port and identify the type of the trial and the start time of each part of the trial. An exaustive explanation can be found in Jaramillo-Gonzalez, Wu, Tonin, et al. (2021), but for reference here is report a summary explanatory table:

Meaning Yes trial No trial Open trial
Session start S9 S9 S9
Baseline S10 S11 S12
Stimulus S5 S6 S7
Response S4 S8 S13
Feedback S1 S2 S3
Session end S15 S15 S15
datacite.yml
Title Auditory Electrooculogram-based Communication System for ALS patient (pt11)
Authors Tonin,Alessandro;Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany
Jaramillo-Gonzalez,Andres;Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany
Rana,Aygul;Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany;orcid.org/0000-0003-2756-945
Khalili-Ardali,Majid;Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany
Birbaumer,Niels;Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany
Chaudhary,Ujwal;Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany; Wyss Center for Bio- and Neuro-Engineering, Geneva, Switzerland;orcid.org/0000-0002-7887-1012
Description This dataset contains electrooculogram (EOG) recordings during use of a non-invasive BCI system previously described in doi:10.1038/s41598-020-65333-1. This dataset comprises only recordings for participant p11, with additional recordings not part of the originally published dataset.
License Creative Commons Attribution-NonCommercial-ShareAlike 4.0 (http://creativecommons.org/licenses/by-nc-sa/4.0/)
References Tonin, A., Jaramillo-Gonzalez, A., Rana, A. et al. Auditory Electrooculogram-based Communication System for ALS Patients in Transition from Locked-in to Complete Locked-in State. Sci Rep 10, 8452 (2020). https://doi.org/10.1038/s41598-020-65333-1 [doi:10.1038/s41598-020-65333-1] (IsDescribedBy)
Verbal Communication using Intracortical Signals in a Completely Locked In-Patient. Ujwal Chaudhary, Ioannis Vlachos, Jonas B. Zimmermann, Arnau Espinosa, Alessandro Tonin, Andres Jaramillo-Gonzalez, Majid Khalili-Ardali, Helge Topka, Jens Lehmberg, Gerhard M. Friehs, Alain Woodtli, John P. Donoghue, Niels Birbaumer. medRxiv 2020.06.10.20122408; doi: https://doi.org/10.1101/2020.06.10.20122408 [doi:10.1101/2020.06.10.20122408] (IsSupplementTo)
Funding Deutsche Forschungsgemeinschaft (DFG) DFG BI 195/77-1
BMBF (German Ministry of Education and Research) 16SV7701
CoMiCon
LUMINOUS-H2020-FETOPEN-2014-2015-RIA (686764)
Wyss Center for Bio and Neuroengineering, Geneva
Keywords Neuroscience
BCI
EOG
brain-computer interface
BMI
brain-machine interface
EEG
human
amyotrophic lateral sclerosis
ALS
Resource Type Dataset