High Frequency Oscillations and spikes: Separating real HFOs from false oscillations
High Frequency Oscillations and spikes: Separating real HFOs from false oscillations
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DOI：
10.1016/j.clinph.2015.04.290
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发表时间：
2016-01-01
影响因子：
4.7
通讯作者：
Gotman, Jean
中科院分区：
文献类型：
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作者：
Amiri, Mina;Lina, Jean-Marc;Gotman, Jean
目的：论证和量化由尖锐事件滤波产生的假高频振荡（HFOs）的发生。通过对原始信号的分析来区分真实的hfo和虚假的hfo。方法：提出了一种新的方法，通过检测原始信号在尖锐事件发生时的振荡来防止由于滤波效应而导致的高频振荡检测错误。在纹波带和快速纹波带中，我们使用支持向量机指定时间特征来对有和没有hfo的尖锐事件进行分类。传统上使用的时频表示法是表示真假hfo的金标准。结果：44%的波纹和43%的FRs合并剧烈事件被发现为假hfo。有hfo的剧烈事件在原始信号中的振荡明显多于没有hfo的剧烈事件。在纹波带和快速纹波带分别以76.6%和72.6%的准确率与假hfo进行了区分。结论：对hfo的检测不仅适用于滤波信号，也适用于原始信号。由于宽带活动可能产生掩蔽效应，用于识别hfo的经典时频显示应谨慎使用。意义：将真实的HFO与宽带活动分离将提高HFO检测方法的有效性，从而支持未来的HFO调查。(C) 2015年国际临床神经生理学联合会。爱思唯尔爱尔兰有限公司出版。版权所有。
Objective: To demonstrate and quantify the occurrence of false High Frequency Oscillations (HFOs) generated by the filtering of sharp events. To distinguish real HFOs from spurious ones using analysis of the raw signal.Method: We developed a new method to prevent false HFO detections due to the filtering effect by detecting oscillations in the raw signal at the time of sharp events. We specified temporal features to classify sharp events with and without HFOs using support vector machine in both ripple and fast ripple bands. The traditionally used time-frequency representation served as the gold standard to indicate real and false HFOs.Results: 44% of ripples and 43% of FRs concurring with sharp events were found to be false HFOs. Sharp events with HFOs had significantly more oscillations in the raw signal than sharp events without. They could be distinguished from false HFOs with accuracy of 76.6% in the ripple band and 72.6% in the fast ripple band.Conclusion: It may be most appropriate to detect HFOs as oscillations not only on the filtered signal but also on the raw signal. The classical time-frequency display used for identifying HFOs should be used with great care due to the possible masking effect of broadband activities.Significance: The separation of real HFOs from broadband activities will raise the validity of HFO detection methods and will therefore support future HFO investigations. (C) 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.