文献类型：期刊文献

英文题名：Automatic detection of Interictal Epileptiform discharges based on the similarity of time-series sequence

作者：Zhang, Jian[1]; Zou, Junzhong[1]; Chen, Lanlan[1]; Zhao, Chenjie[2]; Wang, Guisong[2]

机构：[1] Department of Automation, School of Information Science and Engineering, East China University of Science and Technology, Shanghai 200237, China; [2] Department of Neurosurgery, Renji Hospital Affiliated to Shanghai Jiao Tong University, Shanghai 200233, China

年份：2013

卷号：239-240

起止页码：921

外文期刊名：Applied Mechanics and Materials

收录：EI(收录号：20130215885904)

语种：英文

外文关键词：Database systems - Mergers and acquisitions - Merging - Digital signal processing

摘要：In this paper, an effective digital signal processing method based on the merger of the increasing and decreasing time-series sequences (MIDS) is introduced. On the basis of the merging of EEG signals, a new IED (Interictal Epileptiform Discharges) detection method is proposed. The first step of this new method is to establish a database by selecting peaked wave fragments. Then, the similarity between pending test fragment and peaked wave samples in the database is calculated. When the maximum similarity is greater than a certain threshold, the fragment is judged to be a peaked wave. Finally, the wave type i.e. spike wave, sharp wave, spike-and-slow wave or sharp-and-slow wave can be determined by whether there is a subsequent slow wave or not. Continuous sharp wave can be viewed as spike rhythm. In this research, 92 IED fragments from 4 suspected epilepsy patients are collected to establish the sample database. The proposed method was tested on EEG recordings from other 31 suspected patients. The results show that 98.11% of the IED fragments marked by doctors were detected. The experimental results show that this method performs well at IED detection in the clinical EEG data. The similarity is measured based on the comparison between fragments of different time length and can be viewed as a novel approach for the detection of typical EEG waveform. This research draws two conclusions: (1) the waveform of individual peaked wave is stable during 24-hour EEG recording process; (2) the database containing a small number peaked wave samples can be used to detect IED fragments. ? (2013) Trans Tech Publications, Switzerland.