Title: Engineering modelling for alliance of late potentials in ECG signals in the course of wavelets

Authors: P.V. Rama Raju, V. Malleswara Rao, Ch.V. Satyanarayana

Addresses: Department of Electronics and Communication Engineering, SRKR Engg. College, Bhimavaram 534 204, AP, India; Affiliated to Andhra University, AP, India. ' Department of Electronics and Communication Engineering, SRKR Engg. College, Bhimavaram 534 204, AP, India; Affiliated to Andhra University, AP, India. ' Department of Electronics and Communication Engineering, SRKR Engg. College, Bhimavaram 534 204, AP, India; Affiliated to Andhra University, AP, India

Abstract: Late potentials in ECG take place in the terminal portion of the QRS complex and are characterised by tiny amplitudes and larger frequencies. The occurrence of late potentials may signify underlying distribution of electrical activity of the cells in the heart and provides a substrate for production of arrhythmias (Rama Raju et al., 2008; Rama Raju and Malleswara Rao, 2009a). The problem of late potentials causes high levels of signal power to be seen at frequencies not representing the original signal (Rama Raju et al., 2008; Rama Raju and Malleswara Rao, 2009a). The present work describes the application of wavelet transform to provide a more accurate picture of the localised time-scale features indicative of the late potentials (Addison, 2005). The first step includes generating mathematical equations for various cases by developing a programme in Matlab. Mathematical equations are consequently generated for the signals under consideration and are compared with the available database (Rama Raju et al., 2009, 2010a; Rama Raju and Malleswara Rao, 2009b). The second step includes comparing the signal under consideration with all those signals in the database by developing an identification code in Matlab (Rama Raju et al., 2010c, 2010d). The late potentials in the signals under consideration were analysed and identified (Rama Raju et al., 2010b, 2010c, 2010d). Signals under consideration are represented mathematically and graphically and compared to classify the case more straightforwardly.

Keywords: Fourier transforms; STFT; short-time Fourier transform; CWT; continuous wavelet transform; Wigner-Ville distribution; ECG; electrocardiograms; late potentials; AANSIAMI-EC13 database; St. Petersburg; INCART 12-lead arrhythmia database; heart disease; cardiac arrest; electrical signals.

DOI: 10.1504/IJHTM.2011.042367

International Journal of Healthcare Technology and Management, 2011 Vol.12 No.5/6, pp.353 - 363

Published online: 28 Mar 2015 *

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