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A New Localization Method for Epileptic Seizure Onset Zones Based on Time-Frequency and Clustering Analysis
Pattern Recognition ( IF 8 ) Pub Date : 2021-03-01 , DOI: 10.1016/j.patcog.2020.107687
Min Wu , Ting Wan , Xiongbo Wan , Zelin Fang , Yuxiao Du

Abstract High-frequency oscillations (HFOs) are spontaneous electroencephalogram patterns that have been regarded as potential biomarkers of epileptic seizure onset zones (SOZs). Accurately detected HFOs are used to localize SOZs, which is crucial for the presurgical assessment. Since the visual marking of HFOs is time-consuming, a method is desirable to automatically detect HFOs for localizing SOZs in clinical practice. However, the existing methods cannot obtain satisfactory performance, which are not suitable for clinical application. In order to solve this problem, we present a new localization method for epileptic SOZs in this study. Firstly, a threshold method is used to detect events of interest (EoIs). Secondly, a time-frequency analysis method is adopted to acquire channels of interest (CoIs) by calculating the average power of EoIs on each channel. Then, the k-medoids clustering method is employed to detect HFOs of CoIs. Finally, the concentrations of detected HFOs are used to localize SOZs. The superiority of our localization method is demonstrated by comparing its sensitivity and specificity with some existing methods.

中文翻译:

基于时频聚类分析的癫痫发作区定位新方法

摘要 高频振荡 (HFO) 是自发性脑电图模式,已被视为癫痫发作区 (SOZ) 的潜在生物标志物。准确检测到的 HFO 用于定位 SOZ,这对于术前评估至关重要。由于 HFO 的视觉标记非常耗时,因此需要一种在临床实践中自动检测 HFO 以定位 SOZ 的方法。然而,现有的方法不能获得令人满意的性能,不适合临床应用。为了解决这个问题,我们在本研究中提出了一种新的癫痫 SOZ 定位方法。首先,阈值方法用于检测感兴趣的事件(EoI)。第二,采用时频分析方法,通过计算每个信道上EoI的平均功率,获取感兴趣的信道(CoI)。然后,采用 k-medoids 聚类方法检测 CoI 的 HFO。最后,检测到的 HFO 的浓度用于定位 SOZ。通过将其灵敏度和特异性与一些现有方法进行比较,证明了我们定位方法的优越性。
更新日期:2021-03-01
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