Minimal Representation of Electrocardiogram Signals: Towards Low-Cost Telecardiology

Tamboli, R R and Jana, Soumya (2015) Minimal Representation of Electrocardiogram Signals: Towards Low-Cost Telecardiology. Masters thesis, Indian Institute of Technology Hyderabad.

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Abstract

This thesis seeks methods for minimal linear representation and subsequently low rate sampling of electrocardiogram (ECG) signals. ECG, a non-invasive approach to record heart's electrical activity, has been an ubiquitous tool for preliminary as well as complicated diagnoses of heart related issues. The modern lifestyle of ever increasing population has elevated the rate of heart diseases. Many a times, periodic monitoring of ECG, such as holter monitors, becomes imperative for diagnosis and curing of heart conditions. Some of the major issues in maintaining quality of healthcare services are low doctor to patient ratio in urban as well as resource constrained rural localities, unavailability of trained medical professionals in remote areas, infrastructural constraints etc. In this backdrop, personalized and mobile healthcare, such as telecardiology has been proposed. In order to realize a resource friendly telecardiology system, several engineering aspects need attention. This thesis focuses on a few related signal processing issues. Specifically, compact representation and low rate sampling of ECG signals, subject to certain representation/ reconstruction accuracy are discussed. It is observed that `sym4' and `db4' wavelets pack the energy of various ECG signals in least number of coeficients. Further, the proposed hybrid Fourier/ wavelet method is shown to offer even sparser representation by using Fourier approximation for the low frequency component and wavelet approximation for the remaining part of the signals. The former contains most of the signal energy whereas the latter accounts for key clinical information at feature points. Next, sparsity of ECG signals is exploited to demonstrate near universality of the proposed nonuniform sampling scheme. Recent advances in compressive sensing (CS) theory have facilitated recovery from samples acquired in a nonuniform manner. The evaluation of proposed methods is based on empirical studies on large ECG datasets available publicly. This is justified as proposing a statistical model for ECG signals is difficult on account of wide variety of such signals. Objective quality measures are used to judge the performance.

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