Publication: Automatic detection of high frequency oscillations during epilepsy surgery predicts seizure outcome
Automatic detection of high frequency oscillations during epilepsy surgery predicts seizure outcome
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Fedele, T., van ’t Klooster, M., Burnos, S., Zweiphenning, W., van Klink, N., Leijten, F., Zijlmans, M., & Sarnthein, J. (2016). Automatic detection of high frequency oscillations during epilepsy surgery predicts seizure outcome. Clinical Neurophysiology, 127, 3066–3074. https://doi.org/10.1016/j.clinph.2016.06.009
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OBJECTIVE: High frequency oscillations (HFOs) and in particular fast ripples (FRs) in the post-resection electrocorticogram (ECoG) have recently been shown to be highly specific predictors of outcome of epilepsy surgery. FR visual marking is time consuming and prone to observer bias. We validate here a fully automatic HFO detector against seizure outcome. METHODS: Pre-resection ECoG dataset (N=14 patients) with visually marked HFOs were used to optimize the detector's parameters in the time-frequency domain. The optimized detector
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- Fedele, Tommaso
- van 't Klooster, Maryse
- Burnos, Sergey
- Zweiphenning, Willemiek
- van Klink, Nicole
- Leijten, Frans
- Zijlmans, Maeike
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Fedele, T., van ’t Klooster, M., Burnos, S., Zweiphenning, W., van Klink, N., Leijten, F., Zijlmans, M., & Sarnthein, J. (2016). Automatic detection of high frequency oscillations during epilepsy surgery predicts seizure outcome. Clinical Neurophysiology, 127, 3066–3074. https://doi.org/10.1016/j.clinph.2016.06.009
