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Electrocardiogram (ECG) signals obtained during driving simulations provide an indication of physiological response during complex driving tasks. The present study contributes to the literature on this response through the analysis of features in time-frequency representations, specifically, continuous wavelet transforms (CWTs). The main frequency band in the CWT of ECG signals, which corresponds...
Wavelet entropy is an analysis tool applicable to biomedical signals, including EEG and ECG. The current paper proposes an application of methods from visual analytics to time-frequency energy distribution in ECG signals, with the goal of studying heart rate variability from the main ECG band corresponding to heart rate. Such an approach can complement standard time- and frequency-domain techniques...
The aim of this paper is to use the Continuous Wavelet Transform (CWT) in order to diagnose the pathology that appears in the ECG analysis. The signals used are based on real ECG recordings. The Continuous Wavelet Transform allows a signal represented in the time domain to be represented in time-frequency domain. In this study we used a Normal ECG, an ECG with bradycardia, ECG with tachycardia and...
Ballistocardiography is recognized as a reliable method for non-invasive assessment of cardiovascular functions. In this work, a wavelet approach was used on the y-axis ballistocardiogram (BCG) to evaluate the respiratory sinus arrhythmia (RSA) phenomenon using a new parameter: the ballistocardiogram amplitude modulation induced by respiration (BAMR). Eamax, local maximum energy of BCGy, was quantified...
The 7th Computers in Cardiology challenge presents the clinically important problem of developing and testing fully automated methods for measurement of the QT interval with clinically acceptable accuracy. For this purpose a fully automated method was developed using time-frequency methods of continuous (CWT) and fast wavelet transforms (FWT). It consists of QRS detection and P, T wave boundaries...
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