Classification of artifactual EEG signal and detection of multiple eye movement artifact zones using novel Time-amplitude algorithm

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• 作者：Manish N. Tibdewal ; Rohan R. Fate ; M. Mahadevappa…
• 关键词：Electroencephalogram ; Eye Movement (EM)  Artifacts ; ANN ; Time ; Amplitude (TA)  Algorithm ; Discrete Wavelet Transform (DWT) ; ROC parameters
• 刊名：Signal, Image and Video Processing
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：11
• 期：2
• 页码：333-340
• 全文大小：
• 刊物类别：Engineering
• 刊物主题：Signal,Image and Speech Processing; Image Processing and Computer Vision; Computer Imaging, Vision, Pattern Recognition and Graphics; Multimedia Information Systems;
• 出版者：Springer London
• ISSN：1863-1711
• 卷排序：11

文摘

Electroencephalogram (EEG) signal has numerous applications in the field of medical science. It is used to diagnose many of the abnormalities, disorders, and diseases related to the human brain. The EEG signal contaminated with ocular artifacts makes it very difficult for analysis and diagnosis. This paper includes work on classification of artifactual/non-artifactual EEG time series and perfect detection of eye movement (EM) artifact contaminated EEG signal along with multiple EM artifactual zones in the same time series. Artificial Neural Network classifier in a simple perceptron model without hidden layer is used for the identification. This study presents a newly developed, simple, robust, and computationally fast statistical Time-Amplitude algorithm. By the application of novel Time-Amplitude algorithm on identified signal, the EM artifactual EEG signal along with multiple zones is automatically detected and marked accurately. Such robust, efficient, real-time and simple algorithm is not ever designed and used for ocular artifact detection by any author. The ROC analysis gives accuracy of the ANN model for classifying the presence of artifacts in the EEG data, which is 97.50 %. The time elapsed for executing the Time-Amplitude algorithm for automatic detection of EM artifact is very less (4.30 msec.) compared to DWT with Haar. It has the capability to detect multiple EM artifactual zones, in the same time, for the montage of 8-second EEG.