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.