High frequency oscillations have been recently proposed as a new biomarker of seizure onset zone.Marking epileptic discharge is highly time-consuming,easy to get false detection,and the relation between discharge and seizure still leaves much to define.This paper presents a fast automated detection method based on the difference of power spectral density in each channel,and similarity of filtered signal enveloped on epilepsy propagation path,and also the combination with complex Morlet wavelet transform to classify high frequency oscillations.The results obtained in 4 clinical cases show high performance in terms of sensitivity and specificity which can be considered as an effective method in preoperative locali-zation.%最新研究发现癫痫脑电信号中的高频振荡节律( High-frequency Oscillations,HFOs)是定位癫痫始发区( Sei-zure Onset Zone,SOZ)的重要生物指标.在癫痫致痫灶术前定位的过程中,以癫痫样放电判断癫痫始发区的方法十分耗时,而且癫痫样放电与癫痫发作的关系还不明确,不但增加病人感染疾病的风险,还会造成误诊.本文设计了一种基于高频振荡节律的快速定位算法,利用功率谱密度的差异提取疑似癫痫始发区,再根据曲线模板检出高频振荡节律同步出现的导联;同时基于复Morlet小波将信号变换到时频域进行分析,共同实现癫痫始发区快速定位.经过对4例临床病例处理的结果表明,该算法灵敏度和特异性良好,有助于临床癫痫手术术前精确定位.
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