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Neuro-fuzzy based ECG signal classification with a gaussian derivative filter
Other Title(s)
تصنيف إشارة القلب باعتماد النظام العصبي المضبب و مرشح مشتقة كاوس
Joint Authors
Abd al-Jabbar, Jasim Muhammad
Muhammad, Sima Nizar
Yahya, Hibah Nabil
Source
al-Rafidain Engineering Journal
Issue
Vol. 23, Issue 2 (30 Apr. 2015), pp.62-75, 14 p.
Publisher
University of Mosul College of Engineering
Publication Date
2015-04-30
Country of Publication
Iraq
No. of Pages
14
Main Subjects
Topics
- Heart
- Engineering
- Electrical engineering
- Diseases
- Electrical properties
- Neural networks(Computer science)
- Diagnosis
- Electrocardiography
Abstract AR
في هذا البحث٬ تم استخدام طريقة التصنيف باعتماد (Neuro-fuzzy) لأغراض التعرف على إشارات ECG.
و استعملت طريقة لاستخلاص السمات بالاعتماد على مرشح ذو استجابة بنوع مشتقة كاوس الأولى و التي تشبه تركيبة QRS في إشارة الـ ECG.
تم بعد ذلك استخدام تلك السمات كإدخالات لمنظومة التصنيف باعتماد (Neuro-fuzzy).
إن إشارات ECG المستخدمة في هذا البحث تم الحصول عليها من (The standard MIT-database).
و استخدم منها خمس أنواع هي (NSR)، (LBBB)، (RBBB)، (PVC)، (PM).
إن المنظومة المستخدمة تجمع بين الإمكانات المتكيفة للشبكات العصبية و بين الموائمة الضبابية مع التصميم المناسب للمرشح و هذا أعطى دقة تصنيف واعدة و بنسبة 99 %.
Abstract EN
-In this paper, a neuro-fuzzy classification method is used for identifications of ECG signals.
A feature extraction method with a QRS like filter (first order Gaussian derivative filter) is used.
Five standard parameters (energy, mean value, standard deviation, maximum and minimum) are extracted from these disease features and then used as inputs for the neuro-fuzzy classification system.
The ECG signals are imported from the standard MIT-BIH database.
Five types of ECG signals are used for classification; they are normal sinus rhythm (NSR), left bundle branch block (LBBB), right bundle branch block (RBBB), premature ventricular contraction (PVC) and pacemaker (PM).
The proposed system combines the neural network adaptive capabilities and fuzzy inference system with the suitable filter design to give a promising classification accuracy of 99 %.
American Psychological Association (APA)
Abd al-Jabbar, Jasim Muhammad& Muhammad, Sima Nizar& Yahya, Hibah Nabil. 2015. Neuro-fuzzy based ECG signal classification with a gaussian derivative filter. al-Rafidain Engineering Journal،Vol. 23, no. 2, pp.62-75.
https://search.emarefa.net/detail/BIM-573952
Modern Language Association (MLA)
Abd al-Jabbar, Jasim Muhammad…[et al.]. Neuro-fuzzy based ECG signal classification with a gaussian derivative filter. al-Rafidain Engineering Journal Vol. 23, no. 2 (Apr. 2015), pp.62-75.
https://search.emarefa.net/detail/BIM-573952
American Medical Association (AMA)
Abd al-Jabbar, Jasim Muhammad& Muhammad, Sima Nizar& Yahya, Hibah Nabil. Neuro-fuzzy based ECG signal classification with a gaussian derivative filter. al-Rafidain Engineering Journal. 2015. Vol. 23, no. 2, pp.62-75.
https://search.emarefa.net/detail/BIM-573952
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 75
Record ID
BIM-573952