A comprehensive, physician-trained algorithm to remove artifactual false positive High Frequency Oscillations in long-term intracranial EEG

Key Points

• To develop an algorithm that effectively removes false positive detections of high frequency oscillations (HFOs) in intracranial EEG data.
• Utilized raw intracranial EEG data for HFO detection.
• Designed an algorithm trained by physicians to distinguish between true and false HFO signals.
• Tested the algorithm's effectiveness in various recording environments.
• Successfully removed artifactual false positives in HFO detections.
• Retained adequate numbers of true naHFOs for further analysis.
• Demonstrated adaptability to different HFO detection systems.