کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6900673 1446490 2018 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Ictal EEG Classification based on State Space Modeling of Intrinsic Mode functions
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر علوم کامپیوتر (عمومی)
پیش نمایش صفحه اول مقاله
Ictal EEG Classification based on State Space Modeling of Intrinsic Mode functions
چکیده انگلیسی
The Electroencephalogram signals are characterized by mental status of human body. The electrical activity of this signal is non-linear and non-stationary in nature. In this work, the EEG signal is to undergo empirical mode decomposition which yields a set of intrinsic mode functions. Taking into account the non-linear nature of the EEG signal, state space analysis of the IMFs is carried out, which eventually leads to an outstanding classification into ictal EEG and healthy EEG class. Here Kalman filter is used to take the state estimation of each IMFs. Then temporal and statically features of each IMFs are extracted. The adaptive neuro-fuzzy inference system is used to classify ictal EEG and healthy EEG status. The study shows Teager energy and Kurtosis are 100% accuracy in classification. Apart from this, combination of Kurtosis and standard deviation features shows 100% in sensitivity, specificity and accuracy achieved in classification of different ictal stages.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Procedia Computer Science - Volume 125, 2018, Pages 468-475
نویسندگان
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