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Updated: Oct 19, 2025

Interictal High Frequency Oscillations Detected with Simultaneous Magnetoencephalography and Electroencephalography as Biomarker of Pediatric Epilepsy
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HFOApp: A MATLAB Graphical User Interface for High-Frequency Oscillation Marking.

Guangyu Zhou1, Torben Noto2, Arjun Sharma2

  • 1Department of Neurology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois 60611 guangyu.zhou@northwestern.edu.

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|September 21, 2021
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Summary
This summary is machine-generated.

A new free software, HFOApp, aids in identifying high-frequency oscillations (HFOs) in epilepsy patients. This tool improves speed and accuracy for clinicians and researchers, enhancing surgical planning for difficult-to-treat epilepsy.

Keywords:
MATLABgraphical user interfacehigh-frequency oscillations

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Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Medical Informatics

Background:

  • Epilepsy impacts millions, with many patients experiencing uncontrolled seizures despite medication.
  • High-frequency oscillations (HFOs) are emerging biomarkers for epileptogenic tissue, crucial for surgical planning.
  • Current HFO detection methods are time-consuming, inconsistent, and rely on subjective manual analysis.

Purpose of the Study:

  • To develop an improved, user-friendly software for detecting and marking HFOs.
  • To enhance the speed, accuracy, and reliability of HFO analysis in clinical practice.
  • To provide clinicians and researchers with a free, open-source tool for HFO quantification.

Main Methods:

  • Development of HFOApp, a MATLAB-based graphical user interface.
  • Integration of interactive automation-assist features with manual marking capabilities.
  • Implementation of simultaneous multichannel detection and marking functionalities.

Main Results:

  • HFOApp offers intuitive usability, significantly reducing manual marking and review time.
  • The software increases inter-rater reliability in HFO identification.
  • HFOApp enables quick and accurate marking, quantification, and characterization of HFOs.

Conclusions:

  • HFOApp represents a significant advancement in HFO analysis tools for epilepsy research and clinical application.
  • The software's ease of use, speed, and accuracy address limitations of existing open-source solutions.
  • HFOApp facilitates more efficient and reliable use of HFOs as biomarkers for surgical planning in epilepsy.