کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10345390 | 698264 | 2014 | 15 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A model-based method for computation of correlation dimension, Lyapunov exponents and synchronization from depth-EEG signals
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
علوم کامپیوتر (عمومی)
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: A model-based method for computation of correlation dimension, Lyapunov exponents and synchronization from depth-EEG signals A model-based method for computation of correlation dimension, Lyapunov exponents and synchronization from depth-EEG signals](/preview/png/10345390.png)
چکیده انگلیسی
In order to predict epileptic seizures many precursory features, extracted from the EEG signals, have been introduced. Before checking out the performance of features in detection of pre-seizure state, it is required to see whether these features are accurately extracted. Evaluation of feature estimation methods has been less considered, mainly due to the lack of a ground truth for the real EEG signals' features. In this paper, some simulated long-term depth-EEG signals, with known state spaces, are generated via a realistic neural mass model with physiological parameters. Thanks to the known ground truth of these synthetic signals, they are suitable for evaluating different algorithms used to extract the features. It is shown that conventional methods of estimating correlation dimension, the largest Lyapunov exponent, and phase coherence have non-negligible errors. Then, a parameter identification-based method is introduced for estimating the features, which leads to better estimation results for synthetic signals. It is shown that the neural mass model is able to reproduce real depth-EEG signals accurately; thus, assuming this model underlying real depth-EEG signals, can improve the accuracy of features' estimation.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computer Methods and Programs in Biomedicine - Volume 113, Issue 1, January 2014, Pages 323-337
Journal: Computer Methods and Programs in Biomedicine - Volume 113, Issue 1, January 2014, Pages 323-337
نویسندگان
F. Shayegh, S. Sadri, R. Amirfattahi, K. Ansari-Asl,