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EyeBallGUI: A Tool for Visual Inspection and Binary Marking of Multi-channel Bio-signals

Kieran S. Mohr, View ORCID ProfileBahman Nasseroleslami, View ORCID ProfileParameswaran M. Iyer, View ORCID ProfileOrla Hardiman, View ORCID ProfileEdmund C. Lalor
doi: https://doi.org/10.1101/129437
Kieran S. Mohr
1K. Mohr was with the Academic Unit of Neurology, Trinity College Dublin, the University of Dublin, 152-160 Pearse St., Dublin D02 R590, Ireland.
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Bahman Nasseroleslami
2B. Nasseroleslami is with the Academic Unit of Neurology, Trinity College Dublin, the University of Dublin, Dublin D02 R590, Ireland
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Parameswaran M. Iyer
3P. M. Iyer was with the Academic Unit of Neurology, Trinity College Dublin, the University of Dublin, Dublin D02 R590, Ireland.
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Orla Hardiman
4O. Hardiman is with the the Academic Unit of Neurology, Trinity Biomedical Sciences Institute, Trinity College Dublin, the University of Dublin, Dublin D02 R590, Ireland.
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Edmund C. Lalor
5E. C. lalor was with the Trinity Centre for Bioengineering, Trinity College Dublin, the University of Dublin, Dublin D02 R590, Ireland.
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Abstract

A wide range of studies in human neuroscience rely on the analysis of electrophysiological bio-signals such as electroencephalogram (EEG) where customized data analysis may require supervised artefact rejection, binary marking through visual inspection, selection of noise and artefact samples for pre-processing algorithms, and selection of clinically-relevant signal segments in neurological conditions. Nevertheless, the existing preprocessing tools do not provide the needed flexibility to handle such tasks efficiently. We therefore developed a free open-source Graphical User Interface (GUI), EyeBallGUI, that allows visualization and flexible, manual marking (binary classification) of multi-channel bio-signal data. EyeBallGUI, developed for MATLAB®, allows the user to interactively and accurately inspect and mark multi-channel digitized data with no restriction on marking periods of data in subsets of channels (a restriction in place in existing tools). The new tool facilitates precise, manual marking of bio-signals by allowing any desired segment of data to be marked in any subset of channels. It is therefore of utility in circumstances where such flexibility is essential. The developed GUI is an auxiliary analysis tool that shall facilitate neural signal (pre-)processing applications where it is desirable to perform accurate supervised artefact rejection, flexible data marking for increased data retention yield, extraction of specific signal segments by expert users from sample data, or labeling of data for clinical and scientific research purposes.

Footnotes

  • * Research supported by the Health Research Board (HRB) of Ireland.

  • He is now with the School of Electronic and Electrical Engineering, University College Dublin, Stillorgan Rd, Belfield, Dublin, Ireland (phone: +353 87 6122074; e-mail: mohrk{at}tcd.ie).

  • (email: nasserob{at}tcd.ie).

  • He is now with the Department of Neurology, St. James’s Hospital, Dublin D08 NHY1, Ireland (email: parames68{at}gmail.com).

  • She is also with Beaumont Hospital, D09 V2N0, Ireland (email: hardimao{at}tcd.ie).

  • He is now with the Departments of Neuroscience and Biomedical Engineering, University of Rochester, Rochester, NY 14611, USA (email: edlalor{at}tcd.ie).

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-ND 4.0 International license.
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Posted May 06, 2017.
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EyeBallGUI: A Tool for Visual Inspection and Binary Marking of Multi-channel Bio-signals
Kieran S. Mohr, Bahman Nasseroleslami, Parameswaran M. Iyer, Orla Hardiman, Edmund C. Lalor
bioRxiv 129437; doi: https://doi.org/10.1101/129437
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EyeBallGUI: A Tool for Visual Inspection and Binary Marking of Multi-channel Bio-signals
Kieran S. Mohr, Bahman Nasseroleslami, Parameswaran M. Iyer, Orla Hardiman, Edmund C. Lalor
bioRxiv 129437; doi: https://doi.org/10.1101/129437

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