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Article
ECG Analysis Using DWT and Wavelet Coefficient to Reduce the Feature and SVM-ICP for Classification and Matching

Author: Janan A. Mahdi
Journal: Engineering and Technology Journal مجلة الهندسة والتكنولوجيا ISSN: 16816900 24120758 Year: 2018 Volume: 36 Issue: 8 Part (A) Engineering Pages: 925-929
Publisher: University of Technology الجامعة التكنولوجية

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Abstract

The Electrocardiogram (ECG) considered as one of the important issue in the medical field (hospitals and clinics), which is used to represent the health of a heart. Increasing patients of heart has supposed to design an automatic computerization technique to classify various abnormalities of the heart activities; to reduce the analysis time and detection mistakes. This research focusing on achieve high performance of classifying abnormal ECG by applying different methods. The first method is Discrete Wavelet Transform (DWT) with 4-level to transform the ECG signal and extract the feature extraction and Wavelet Energy (WE) during feature extraction as feature vector. In classification phase has used Support Vector Machine (SVM) to train datasets and classify the test samples, in matching phase, find closest vector of test to the training datasets method has used by applying Iterative Closest Point (ICP).

Keywords

ECG --- DWT --- Wavelet Energy --- SVM --- ICP


Article
Heartbeat Amplification and ECG Drawing from Video (Black and White or Colored Videos)

Authors: Ahmed A. Shkara --- Yossra Hussain
Journal: Iraqi Journal of Science المجلة العراقية للعلوم ISSN: 00672904/23121637 Year: 2018 Volume: 58 Issue: 1B Pages: 408-419
Publisher: Baghdad University جامعة بغداد

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Abstract

Electrocardiography (ECG or EKG) is the process of recording the electrical activity of the heart over a period of time using electrodes placed on the skin. The main idea is how to detect activity of the heart from skin that appears in video without using electrodes. This paper, proposes an algorithm that works on analyzing video frames to detect heartbeats from tiny changes that happen in a skin color luminance (brightness) and then using them to amplifying heartbeat and drawing ECG. The results show that the heartbeat was detected and amplified and ECG was drawing from any part of the human body in different situations and from different video.


Article
Heartbeat Amplification and ECG Drawing from Video (Black and White or Colored Videos)
تضخيم نبضات القلب ورسم تخطيط القلب (ECG) من الفيديو ( فيديوهات اسود وابيض أو ملون )

Authors: Ahmed A. Shkara --- Yossra Hussain يسرى حسين
Journal: Iraqi Journal of Science المجلة العراقية للعلوم ISSN: 00672904/23121637 Year: 2018 Volume: 58 Issue: 1B Pages: 408-419
Publisher: Baghdad University جامعة بغداد

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Abstract

Electrocardiography (ECG or EKG) is the process of recording the electrical activity of the heart over a period of time using electrodes placed on the skin. The main idea is how to detect activity of the heart from skin that appears in video without using electrodes. This paper, proposes an algorithm that works on analyzing video frames to detect heartbeats from tiny changes that happen in a skin color luminance (brightness) and then using them to amplifying heartbeat and drawing ECG. The results show that the heartbeat was detected and amplified and ECG was drawing from any part of the human body in different situations and from different video.


Article
Feature Extraction and Classification for ECG signals Processing based on Stationary Multiwavelet Transform and Artificial Neural Network
أستخلاص الميزّات والخواص و تصنيفها من اشارة القلب بلاعتماد على الشبكة المتعددة المويجات المستقرة و الشبكه العصبية الصناعية

Author: Zahraa K. Taha زهراء خضير طه
Journal: AL-MANSOUR JOURNAL مجلة المنصور ISSN: 18196489 Year: 2018 Issue: 29 Pages: 85-101
Publisher: Private Mansour college كلية المنصور الاهلية

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Abstract

This paper proposes an algorithm that uses mix of Stationary Multiwavelet Transform and Artificial Neural Network (ANN) algorithm for classification of Electrocardiograph (ECG) signals. The MIT-BIH arrhythmia database is used to measure the performance of the suggested method and compare the results with conventional techniques. The Stationary Multiwavelet Transform (SMWT) and the Minimum Average Maximum strategy (MAM) is suggested to calculate the useful features of the signal before utilizing ANN algorithm for classification. Since SMWT is a translation invariant, therefore, it enhances the classification performance and reduces mean square error (MSE). Repeated Row Processing exists in this scheme to make it more suitable for feature extraction compared with Stationary Wavelet Transform (SWT), Multiwavelet Transform (MWT) and Principle Component Analysis (PCA). SMWT and MAM reduce dimensional space and decrease the complexity of classification circuit. ECG signal is classified using ANN. Finally, the results of the proposed method are realistic compared with SWT-ANN, MWT-ANN, and PCA-ANN. The obtained results emphasize the excellence of the presented algorithm than the traditional techniques. The SMWT-ANN achieves classification accuracy of 100% and mean square error of 〖1.4*10〗^(-3).

تم في هذا البحث الدمج بين الشبكة المتعددة المويجات المستقرة و الشبكه العصبية الصناعية لغرض تصنيف اشارة القلب. ان قاعدة البيانات MIT-BIH قد استخدمت لقياس أداء الطريقة المقترحة ومقارنة النتيجة مع التقنيات التقليدية. ان الطرق (SMWT) و (MAM) تم اقتراحها لاستخلاص الميزّات والخواص من الاشارة قبل تصنيفها بواسطة ANN. بما ان SMWT لها خاصية عدم التغير مع الزحف فأن هذا يعزز من أداء عملية التصنيف ويقلل من الخطأ. أن تكرار معالجة الأسطر الموجودة في هذا المخطط جعل الاسلوب المستخدم أكثر ملاءمة لأستخراج الميزات مقارنة مع SWT, MWT وPCA. ان الطرق (SMWT) و (MAM) تقلل من ابعاد الإشارة وتقلل من تعقيد دائرة التصنيف. أخيراً ان نتائج الطريقة المقترحة هي واقعية مقارنة مع SWT-ANN, MWT-ANNو PCA-ANN. النتائج التي تم الحصول عليها تؤكد تفوق الخوارزمية المقترحة على الاساليب التقليدية.SMWT-ANN حققت دقة تصنيف 100% و معدل خطأ بمقدار 0.0014.


Article
Calculation of Heart Rate Variation Owing to the Effect of Electromagnetic Fields Waves (EMF)
حساب معدل اختلاف ضربات القلب بسبب تأثير مجالات الموجات الكهرومغناطيسية

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Abstract

The chemical reactions that Occur as part of the normal body functions, generated tiny electrical current in the human body. Even in the absence of external electric fields so that exposure to external radiation causes high impact on the nerves signals by transmitting electric impulses. The heart is electrically active and its actons can be measured using an electrocardiogram. Noted slight variation in heart rate may cause serious effects on the human body. The field of electromagnetic emitted from advanced phones has been effect on work of the human heart. In this research taken samples were subjected to examination with presence of phone devices in normal mode and case of vibration when ringing. The study was carried out by taking electrocardiogram (ECG) for group of samples (students) to study the EMF effect of modern phones. After viewing ECG results this area of radiation is shown to cause a negative long-term effect. This effect will be obvious to the human heart and to other parts of its body. http://dx.doi.org/10.31257/2018/JKP/100207

التفاعلات الكيميائية التي تحدث كجزء من وظائف الجسم الطبيعية ، تولد تيار كهربائي صغيرة جدا في جسم الإنسان, حتى في غياب الحقول الكهربائية الخارجية . التعرض للإشعاع الخارجي يسبب تأثير كبير على النبضات الكهربائية الناقلة للإشارات العصبية. القلب نشط كهربائيا ويمكن قياس أفعاله باستخدام جهاز تخطيط القلب (electrocardiogram). التغير الطفيف الملحوظ في معدل ضربات القلب قد يسبب تأثيرات خطيرة على جسم الإنسان. المجال الكهرومغناطيسي المنبعث من الهواتف المتطوره تؤثر على عمل قلب الانسان. في هذا البحث اخضعت العينات للفحص مع وجود أجهزة الهاتف في الوضع العادي وحالة الاهتزاز عند الرنين. أجريت الدراسة عن طريق أخذ تخطيط القلب (ECG) لمجموعة من العينات (طلبة) لدراسة تأثير المجالات الكهرومغناطيسية (EMF) للهواتف النقالة الحديثة. بعد عرض نتائج جهاز تخطيط القلب ظهر أن هذه المنطقة من الإشعاع ( الموجات الصادرة من الاجهزة النقالة ) تسبب تأثير سلبي على المدى الطويل. سيكون التأثير واضحاً على قلب الإنسان و على أجزاء أخرى من جسمه.

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