Cross Wavelet Transform Based Analysis of Electrocardiogram Signals
نویسنده
چکیده
This paper presents a method for analysis of ECG patterns using Cross Wavelet Transform (XWT) and Wavelet Coherence (WCOH) techniques. The cross-correlation is the measure of similarity between two waveforms. The application of the Continuous Wavelet Transform to two time series and the cross examination of the two decomposition reveals localized similarities in time and scale. Morlet wavelet is used as the mother wavelet. A pathologically varying pattern in QT zone of inferior lead III shows the presence of Inferior Myocardial Infarction (IMI). The Cross Wavelet Transform and Wavelet Coherence is used for the cross examination of normal and abnormal (IMI) beats. A normal beat template is selected as the absolute normal pattern and the coherence between various other normal and abnormal is computed. The Wavelet cross spectrum and Wavelet coherence of various ECG patterns shows distinguishing characteristics over two specific regions R1 and R2, where R1 is the QRS complex area and R2 is the T wave region. These obtained results further opens scopes for extraction of appropriate parameter(s) for classification of normal and abnormal data.
منابع مشابه
An Emotion Recognition Approach based on Wavelet Transform and Second-Order Difference Plot of ECG
Emotion, as a psychophysiological state, plays an important role in human communications and daily life. Emotion studies related to the physiological signals are recently the subject of many researches. In This study a hybrid feature based approach was proposed to examine affective states. To this effect, Electrocardiogram (ECG) signals of 47 students were recorded using pictorial emotion elici...
متن کاملFusion Framework for Emotional Electrocardiogram and Galvanic Skin Response Recognition: Applying Wavelet Transform
Introduction To extract and combine information from different modalities, fusion techniques are commonly applied to promote system performance. In this study, we aimed to examine the effectiveness of fusion techniques in emotion recognition. Materials and Methods Electrocardiogram (ECG) and galvanic skin responses (GSR) of 11 healthy female students (mean age: 22.73±1.68 years) were collected ...
متن کاملAdaptive Filtering Strategy to Remove Noise from ECG Signals Using Wavelet Transform and Deep Learning
Introduction: Electrocardiogram (ECG) is a method to measure the electrical activity of the heart which is performed by placing electrodes on the surface of the body. Physicians use observation tools to detect and diagnose heart diseases, the same is performed on ECG signals by cardiologists. In particular, heart diseases are recognized by examining the graphic representation of heart signals w...
متن کاملAdaptive Filtering Strategy to Remove Noise from ECG Signals Using Wavelet Transform and Deep Learning
Introduction: Electrocardiogram (ECG) is a method to measure the electrical activity of the heart which is performed by placing electrodes on the surface of the body. Physicians use observation tools to detect and diagnose heart diseases, the same is performed on ECG signals by cardiologists. In particular, heart diseases are recognized by examining the graphic representation of heart signals w...
متن کاملQuality-Controlled Compression Method using Wavelet Transform for Electrocardiogram Signals
This paper presents a new Quality-Controlled, wavelet based, compression method for electrocardiogram (ECG) signals. Initially, an ECG signal is decomposed using the wavelet transform. Then, the resulting coefficients are iteratively thresholded to guarantee that a predefined goal percent root mean square difference (GPRD) is matched within tolerable boundaries. The quantization strategy of ext...
متن کامل