scholarly journals MEEGIPS—A Modular EEG Investigation and Processing System for Visual and Automated Detection of High Frequency Oscillations

2019 ◽  
Vol 13 ◽  
Author(s):  
Peter Höller ◽  
Eugen Trinka ◽  
Yvonne Höller
Keyword(s):  
High Frequency ◽  
Processing System ◽  
Automated Detection ◽  
High Frequency Oscillations

scholarly journals High-Frequency Oscillations in the Scalp Electroencephalogram: Mission Impossible without Computational Intelligence

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Peter Höller ◽  
Eugen Trinka ◽  
Yvonne Höller
Keyword(s):  
High Frequency ◽  
Visual Detection ◽  
Signal To Noise Ratio ◽  
Physiological Activity ◽  
Automated Detection ◽  
Detection Algorithms ◽  
Scalp Eeg ◽  
High Frequency Oscillations ◽  
Scalp Electroencephalogram ◽  
Electroencephalogram Eeg

High-frequency oscillations (HFOs) in the electroencephalogram (EEG) are thought to be a promising marker for epileptogenicity. A number of automated detection algorithms have been developed for reliable analysis of invasively recorded HFOs. However, invasive recordings are not widely applicable since they bear risks and costs, and the harm of the surgical intervention of implantation needs to be weighted against the informational benefits of the invasive examination. In contrast, scalp EEG is widely available at low costs and does not bear any risks. However, the detection of HFOs on the scalp represents a challenge that was taken on so far mostly via visual detection. Visual detection of HFOs is, in turn, highly time-consuming and subjective. In this review, we discuss that automated detection algorithms for detection of HFOs on the scalp are highly warranted because the available algorithms were all developed for invasively recorded EEG and do not perform satisfactorily in scalp EEG because of the low signal-to-noise ratio and numerous artefacts as well as physiological activity that obscures the tiny phenomena in the high-frequency range.

Automated detection and classification of high frequency oscillations (HFOs) in human intracereberal EEG

2013 ◽  
Vol 8 (6) ◽  
pp. 927-934 ◽  
Author(s):  
Sahbi Chaibi ◽  
Zied Sakka ◽  
Tarek Lajnef ◽  
Mounir Samet ◽  
Abdennaceur Kachouri
Keyword(s):  
High Frequency ◽  
Automated Detection ◽  
High Frequency Oscillations

Intracerebrally recorded high frequency oscillations: Simple visual assessment versus automated detection

2013 ◽  
Vol 124 (10) ◽  
pp. 1935-1942 ◽  
Author(s):  
Martin Pail ◽  
Josef Halámek ◽  
Pavel Daniel ◽  
Robert Kuba ◽  
Ivana Tyrlíková ◽  
...  
Keyword(s):  
High Frequency ◽  
Visual Assessment ◽  
Automated Detection ◽  
High Frequency Oscillations

Automated detection of high-frequency oscillations in electrophysiological signals: Methodological advances

2016 ◽  
Vol 110 (4) ◽  
pp. 316-326 ◽  
Author(s):  
Miguel Navarrete ◽  
Jan Pyrzowski ◽  
Juliana Corlier ◽  
Mario Valderrama ◽  
Michel Le Van Quyen
Keyword(s):  
High Frequency ◽  
Automated Detection ◽  
High Frequency Oscillations ◽  
Electrophysiological Signals

scholarly journals Human and automated detection of high-frequency oscillations in clinical intracranial EEG recordings

2007 ◽  
Vol 118 (5) ◽  
pp. 1134-1143 ◽  
Author(s):  
Andrew B. Gardner ◽  
Greg A. Worrell ◽  
Eric Marsh ◽  
Dennis Dlugos ◽  
Brian Litt
Keyword(s):  
High Frequency ◽  
Automated Detection ◽  
Intracranial Eeg ◽  
High Frequency Oscillations ◽  
Eeg Recordings
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