Article ID Journal Published Year Pages File Type
6007269 Clinical Neurophysiology 2016 9 Pages PDF
Abstract

•Sampling rate and anti-aliasing filters (AAF) affect High Frequency Oscillation (HFO) detection.•Sampling rate ⩾2 kHz and AAF ⩾500 Hz should be used to analyze HFOs; lower settings are still useful.•Calculating peak HFO frequency is unreliable and highly dependent upon the sampling rate.

ObjectiveHigh Frequency Oscillations (HFOs) are being studied as a biomarker of epilepsy, yet it is unknown how various acquisition parameters at different centers affect detection and analysis of HFOs. This paper specifically quantifies effects of sampling rate (FS) and anti-aliasing filter (AAF) positions on automated HFO detection.MethodsHFOs were detected on intracranial EEG recordings (17 patients) with 5 kHz FS. HFO detection was repeated on downsampled and/or filtered copies of the EEG data, mimicking sampling rates and low-pass filter settings of various acquisition equipment. For each setting, we compared the HFO detection sensitivity, HFO features, and ability to identify the ictal onset zone.ResultsThe relative sensitivity remained above 80% for either FS ⩾2 kHz or AAF ⩾500 Hz. HFO feature distributions were consistent (AUROC < 0.7) down to 1 kHz FS or 200 Hz AAF. HFO rate successfully identified ictal onset zone over most settings. HFO peak frequency was highly variable under most parameters (Spearman correlation < 0.5).ConclusionsWe recommend at least FS ⩾2 kHz and AAF ⩾500 Hz to detect HFOs. Additionally, HFO peak frequency is not robust at any setting: the same HFO event can be variably classified either as a ripple (<200 Hz) or fast ripple (>250 Hz) under different acquisition settings.SignificanceThese results inform clinical centers on requirements to analyze HFO rates and features.

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