Epileptic Seizure Detection in Long-Term EEG Recordings by Using Wavelet-Based Directed Transfer Function
Epileptic Seizure Detection in Long-Term EEG Recordings by Using Wavelet-Based Directed Transfer Function
复制标题
使用基于小波的定向传递函数进行长期脑电图记录中的癫痫发作检测
DOI：
10.1109/tbme.2018.2809798
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发表时间：
2018-11-01
影响因子：
4.6
通讯作者：
Wang, Gang
中科院分区：
文献类型：
--
作者：
Wang, Dong;Ren, Doutian;Wang, Gang
目的：癫痫发作的准确自动检测在长时程脑电图（EEG）记录中非常重要。本研究将小波分解和定向传递函数（DTF）算法相结合，提出了一种新颖的基于小波的定向传递函数（WDTF）方法，用于患者特定癫痫发作的检测。方法：首先对19导脑电信号进行滑动窗口小波分解，提取5个子带;其次，利用DTF方法计算了脑电信号五个子带和全频带的信息流特征。然后使用流出信息的强度来降低特征维数。最后，结合所有特征，通过支持向量机分类器识别发作间期和发作期脑电片段。结果如下：通过五重交叉验证，该方法的平均准确率为99.4%，平均选择性为91.1%，平均灵敏度为92.1%，平均特异性为99.5%，平均检出率为95.8%。结论：WDTF方法能够提高局灶性癫痫患者长时程EEG记录中癫痫发作的检测结果。 重要性：本研究将有助于开发高性能的癫痫发作检测系统，从而减轻癫痫医生的工作量，并有助于在癫痫发作后及时采取相应措施。癫痫脑内的高频活动对探讨癫痫的病理机制和治疗具有重要意义。
Goal: The accurate automatic detection of epileptic seizures is very important in long-term electroencephalogram (EEG) recordings. In this study, the wavelet decomposition and the directed transfer function (DTF) algorithm were combined to present a novel wavelet-based directed transfer function (WDTF) method for the patient-specific seizure detection. Methods: First, five subbands were extracted from 19-channel EEG signals by using wavelet decomposition in a sliding window. Second, the information flow characteristics of five subbands and full frequency band of EEG signals were calculated by the DTF method. The intensity of the outflow information was then used to reduce the feature dimensionality. Finally, all features were combined to identify interictal and ictal EEG segments by the support vector machine classifier. Results: By using fivefold cross validation, the proposed method had achieved excellent performance with the average accuracy of 99.4%, the average selectivity of 91.1%, the average sensitivity of 92.1%, the average specificity of 99.5%, and the average detection rate of 95.8%. Conclusion: The WDTF method is able to enhance seizure detection results in long-term EEG recordings of focal epilepsy patients. Significance: This study may lead to the development of seizure detection system with high performance, thus reducing the workload of epileptologists and facilitating to take corresponding steps promptly after the seizure onset. The high-frequency activity in the epilepsy brain may be of great importance for investigating the pathological mechanism and treatment of seizure.