Evaluation of High-Frequency Oscillations Detected by a Novel Signal Analysis Algorithm on Scalp Electroencephalography for Differentiating Patients With Epilepsy From Healthy Controls
Evaluation of High-Frequency Oscillations Detected by a Novel Signal Analysis Algorithm on Scalp Electroencephalography for Differentiating Patients With Epilepsy From Healthy Controls
This observational case-control study aims to evaluate whether high-frequency oscillations (HFOs) detected on scalp electroencephalography (EEG) can differentiate patients with epilepsy from healthy controls. A signal-processing algorithm was developed to identify HFO activity in scalp EEG recordings, with particular focus on ripple (80-250 Hz) and fast ripple (250-500 Hz) frequency bands. Scalp EEG recordings obtained from patients with epilepsy and healthy controls are analyzed after preprocessing and filtering steps. The main outcome is the mean residence time of HFO-related activity above a predefined threshold in the ripple and fast ripple bands. The study investigates whether this noninvasive EEG-based approach may provide a useful biomarker for epilepsy diagnosis.
Inclusion Criteria:
Adults diagnosed with epilepsy
Availability of routine awake scalp EEG recording suitable for analysis
EEG recorded with the study protocol and technical specifications
Inclusion Criteria for Control Group
Adults without epilepsy
Referred for EEG evaluation in the context of syncope differential diagnosis
Scalp EEG recording suitable for analysis
Exclusion Criteria:
Individuals not meeting study group definitions