Successful epilepsy surgeries depend highly on pre-operative localization of epileptogenic zones. Stereoelectroencephalography (SEEG) records interictal and ictal activities of the epilepsy in order to precisely find and localize epileptogenic zones in clinical practice. While it is difficult to find distinct ictal onset patterns generated the seizure onset zone from SEEG recordings in a confined region, high frequency oscillations are commonly considered as putative biomarkers for the identification of epileptogenic zones. Therefore, automatic and accurate detection of high frequency oscillations in SEEG signals is crucial for timely clinical evaluation. This work formulates the detection of high frequency oscillations as a signal segment classification problem and develops a hypergraph-based detector to automatically detect high frequency oscillations such that human experts can visually review SEEG signals. We evaluated our method on 4,000 signal segments from clinical SEEG recordings that contain both ictal and interictal data obtained from 19 patients who suffer from refractory focal epilepsy. The experimental results demonstrate the effectiveness of the proposed detector that can successfully localize interictal high frequency oscillations and outperforms multiple peer machine learning methods. In particular, the proposed detector achieved 90.7% in accuracy, 80.9% in sensitivity, and 96.9% in specificity.

中文翻译：

---

通过超图学习检测癫痫性立体脑电图的高频振荡

成功的癫痫手术高度依赖于癫痫发生区的术前定位。立体脑电图（SEEG）记录癫痫发作的发作和发作活动，以便在临床实践中精确发现和定位癫痫发生区。虽然很难在狭窄区域中从SEEG记录中找到引起发作发作区的独特发作模式，但高频振荡通常被认为是鉴定癫痫发作区的假定生物标记。因此，自动准确地检测SEEG信号中的高频振荡对于及时进行临床评估至关重要。这项工作将高频振荡的检测公式化为信号段分类问题，并开发了基于超图的检测器来自动检测高频振荡，以便人类专家可以直观地查看SEEG信号。我们评估了来自临床SEEG记录的4,000个信号段的方法，该记录包含从19例难治性局灶性癫痫患者中获得的发作和发作间数据。实验结果证明了所提出的检测器的有效性，该检测器可以成功定位局部高频振荡并优于多种对等机器学习方法。特别是，提出的检测器的准确度达到90.7％，灵敏度达到80.9％，特异性达到96.9％。我们评估了来自临床SEEG记录的4,000个信号段的方法，该记录包含从19例难治性局灶性癫痫患者中获得的发作和发作间数据。实验结果证明了所提出的检测器的有效性，该检测器可以成功定位局部高频振荡并优于多种对等机器学习方法。特别是，提出的检测器的准确度达到90.7％，灵敏度达到80.9％，特异性达到96.9％。我们评估了来自临床SEEG记录的4,000个信号段的方法，该记录包含从19例难治性局灶性癫痫患者中获得的发作和发作间数据。实验结果证明了所提出的检测器的有效性，该检测器可以成功定位局部高频振荡并优于多种对等机器学习方法。特别是，提出的检测器的准确度达到90.7％，灵敏度达到80.9％，特异性达到96.9％。实验结果证明了所提出的检测器的有效性，该检测器可以成功定位局部高频振荡并优于多种对等机器学习方法。特别是，提出的检测器的准确度达到90.7％，灵敏度达到80.9％，特异性达到96.9％。实验结果证明了所提出的检测器的有效性，该检测器可以成功定位局部高频振荡并优于多种对等机器学习方法。特别是，提出的检测器的准确度达到90.7％，灵敏度达到80.9％，特异性达到96.9％。