<h1>EEG During Mental Arithmetic Tasks</h1>

<h2>Creators</h2>

<ul>

<li>Igor Zyma</li>

<li>Ivan Seleznov</li>

<li>Anton Popov</li>

<li>Mariia Chernykh</li>

<li>Oleksii Shpenkov</li>

</ul>

<h2>Publication</h2>

<p><strong>Published:</strong> Dec. 17, 2018. <strong>Version:</strong> 1.0.0</p>

<h2>Citations</h2>

<p>Please cite the original publication:</p>

<p>Zyma I, Tukaev S, Seleznov I, Kiyono K, Popov A, Chernykh M, Shpenkov O. Electroencephalograms during Mental Arithmetic Task Performance. Data. 2019; 4(1):14. <a href="https://doi.org/10.3390/data4010014" target="_blank">https://doi.org/10.3390/data4010014</a></p>

<p>Also include the standard PhysioNet citation:</p>

<p>Goldberger, A., Amaral, L., Glass, L., Hausdorff, J., Ivanov, P. C., Mark, R., ... & Stanley, H. E. (2000). PhysioBank, PhysioToolkit, and PhysioNet: Components of a new research resource for complex physiologic signals. Circulation [Online]. 101 (23), pp. e215–e220.</p>

<h2>Introduction</h2>

<p>The database contains EEG recordings of subjects before and during the performance of mental arithmetic tasks.</p>

<h2>Study Methods</h2>

<ul>

<li>EEGs were recorded monopolarly using the Neurocom EEG 23-channel system (Ukraine, XAI-MEDICA).</li>

<li>Electrodes were placed according to the International 10/20 scheme, referenced to interconnected ear electrodes.</li>

<li>High-pass filter: 30 Hz cut-off. Power line notch filter: 50 Hz.</li>

<li>Recordings are 60 seconds long, artifact-free segments. Artifacts were removed using Independent Component Analysis (ICA).</li>

<li>The mental task was serial subtraction of two orally communicated numbers (4-digit minus 2-digit).</li>

<li>Participants had normal cognitive/visual status; exclusion criteria included psychiatric/neurological issues and substance abuse.</li>

</ul>

<h2>Data Description</h2>

<ul>

<li>Data provided in EDF format.</li>

<li>Each subject has two files:

  <ul>

    <li><code>_1</code>: Background EEG (before task).</li>

    <li><code>_2</code>: EEG during mental arithmetic task.</li>

  </ul>

</li>

<li>Datetime set to Jan 01 for all files.</li>

<li>Subjects divided into two groups:

  <ul>

    <li><strong>Group "G"</strong> (24 subjects): Good quality counting (Mean: 21 operations/4 min).</li>

    <li><strong>Group "B"</strong> (12 subjects): Poor quality counting (Mean: 7 operations/4 min).</li>

  </ul>

</li>

<li><code>subject-info.csv</code> contains:

  <ul>

    <li>Gender</li>

    <li>Age</li>

    <li>Occupation</li>

    <li>Date of recording</li>

    <li>Count quality (0: Poor, 1: Good)</li>

  </ul>

</li>

</ul>

<h2>File Access and Viewing</h2>

<p>EDF files can be viewed using:</p>

<ul>

<li>Polyman (Windows only)</li>

<li>EDFbrowser (Linux, macOS, Windows) — <a href="http://www.teuniz.net/edfbrowser/" target="_blank">www.teuniz.net</a></li>

<li>LightWAVE and PhysioBank ATM (web-based, platform-independent)</li>

<li>WAVE and other WFDB Software tools</li>

</ul>

<p>For Python users, recommended library: <a href="https://github.com/holgern/pyedflib/tree/master/pyedflib" target="_blank">PyEDFlib</a>.</p>

<h2>Contributors</h2>

<p>National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", Department of Electronic Engineering:</p>

<ul>

<li>Igor Zyma</li>

<li>Sergii Tukaev</li>

<li>Ivan Seleznov</li>

</ul>

<h2>Contact</h2>

<p>For more information:</p>

<p><strong>Ivan Seleznov</strong><br/>

National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", Department of Electronic Engineering.<br/>

Email: <a href="mailto:ivan.seleznov1@gmail.com">ivan.seleznov1@gmail.com</a></p>