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Cardiac Arrhythmia Detection By ECG Feature Extraction
"... Electrocardiogram (ECG) is a noninvasive technique used as a primary diagnostic tool for detecting cardiovascular diseases. One of the important cardiovascular diseases is cardiac arrhythmia. Computer-assisted cardiac arrhythmia detection and classification can play a significant role in the managem ..."
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Electrocardiogram (ECG) is a noninvasive technique used as a primary diagnostic tool for detecting cardiovascular diseases. One of the important cardiovascular diseases is cardiac arrhythmia. Computer-assisted cardiac arrhythmia detection and classification can play a significant role
Recognition of Cardiac Arrhythmias by Means of Beat Clustering on ECG-Holter Records
"... The follow-up of some cardiac diseases may be achieved by ECG-holter record analysis. A heartbeat clustering method can be used to reduce the usually high computational cost of such holter analysis. This study describes a method aimed at cardiac arrhythmia recognition based on this approach, by mean ..."
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The follow-up of some cardiac diseases may be achieved by ECG-holter record analysis. A heartbeat clustering method can be used to reduce the usually high computational cost of such holter analysis. This study describes a method aimed at cardiac arrhythmia recognition based on this approach
Impact of psychological factors on the pathogenesis of cardiovascular disease and implications for therapy. Circulation
, 1999
"... The online version of this article, along with updated information and services, is located on the ..."
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Cited by 343 (0 self)
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The online version of this article, along with updated information and services, is located on the
1 Classification of cardiac arrhythmia with respect to ECG and HRV signal by genetic programming
"... Abstract — Consistent or periodical heart rhythm disorders may result cardiac arrhythmias. In this article, heart rate variability (HRV) signals are analyzed and various features including time domain, frequency domain and nonlinear parameters are extracted. Moreover, additional nonlinear features a ..."
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are extracted from electrocardiogram (ECG) signals. These features are helpful in classifying cardiac arrhythmias. In this paper, genetic programming is applied to classify heart arrhythmias using both HRV and ECG features. Genetic programming selects effective features, and then finds the most suitable trees
A Patient-Adaptive Profiling Scheme for ECG Beat Classification
"... Abstract—Recent trends in clinical and telemedicine applications highly demand automation in electrocardiogram (ECG) signal processing and heart beat classification. A patient-adaptive cardiac profiling scheme using repetition-detection concept is proposed in this paper. We first employ an efficient ..."
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Cited by 5 (1 self)
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Abstract—Recent trends in clinical and telemedicine applications highly demand automation in electrocardiogram (ECG) signal processing and heart beat classification. A patient-adaptive cardiac profiling scheme using repetition-detection concept is proposed in this paper. We first employ
JDL Fusion Model for ECG Arrhythmia Detection
"... In this paper a novel quick automatic method is proposed for electrocardiogram (ECG). Signal classification to three classes include: the normal heart beats from the left bundle branch block (LBBB), right bundle branch block (RBBB), and paced beats. After noise reduction using wavelet threshold, app ..."
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In this paper a novel quick automatic method is proposed for electrocardiogram (ECG). Signal classification to three classes include: the normal heart beats from the left bundle branch block (LBBB), right bundle branch block (RBBB), and paced beats. After noise reduction using wavelet threshold
An Association Rule Mining-Based Methodology for Automated Detection of Ischemic ECG Beats
"... Abstract—Currently, an automated methodology based on as-sociation rules is presented for the detection of ischemic beats in long duration electrocardiographic (ECG) recordings. The pro-posed approach consists of three stages. 1) Preprocessing: Noise is removed and all the necessary ECG features are ..."
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Abstract—Currently, an automated methodology based on as-sociation rules is presented for the detection of ischemic beats in long duration electrocardiographic (ECG) recordings. The pro-posed approach consists of three stages. 1) Preprocessing: Noise is removed and all the necessary ECG features
BEAT-TO-BEAT P AND T WAVE DELINEATION IN ECG SIGNALS USING A MARGINALIZED PARTICLE FILTER
"... The delineation of P and T waves is important for the interpretation of ECG signals. In this work, we propose a sequential Bayesian detection-estimation algorithm for simultaneous P and T wave de-tection, delineation, and waveform estimation on a beat-to-beat ba-sis. Our method is based on a dynamic ..."
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The delineation of P and T waves is important for the interpretation of ECG signals. In this work, we propose a sequential Bayesian detection-estimation algorithm for simultaneous P and T wave de-tection, delineation, and waveform estimation on a beat-to-beat ba-sis. Our method is based on a
Results 1 - 10
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