A comprehensive, physician-trained algorithm to remove artifactual false positive High Frequency Oscillations in long-term intracranial EEG
MIAF effectively removes false positives HFO detections while retaining sufficient naHFOs for downstream analysis. Because it relies only on raw intracranial data during HFO detections, it can be easily ported to other HFO detectors and recording environments.
Authors
- S. Gliske (ORCID: https://orcid.org/0000-0002-2259-2612)
- Wesley T. Kerr (ORCID: https://orcid.org/0000-0002-5546-5951)
- Neha Sara John (ORCID: https://orcid.org/0000-0003-2415-5296)
- Nicholas J. Beimer (ORCID: https://orcid.org/0000-0002-8054-5769)
- Temenuzhka Mihaylova (ORCID: https://orcid.org/0000-0002-9323-5823)
- Nancy McNamara (ORCID: https://orcid.org/0000-0002-2608-5247)
- Garnett Smith (ORCID: https://orcid.org/0000-0001-7171-8333)
- Shi Bei Tan
- William C Stacey
- Erin Fedak Fedak
Institutions
- Nebraska Medical Center (US)
- University of Michigan (US)
- Michigan Medicine (US)
- Ann Arbor VA Medical Center (US)
- University of Pittsburgh Medical Center (US)
- University of Nebraska Medical Center (US)
Publication Details
- Journal
- Journal of Neural Engineering
- Published
- 2026-03-12
- DOI
- https://doi.org/10.1088/1741-2552/ae512b
- Primary Topic
- Epilepsy research and treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Institutes of Health