Compression of electrocardiograms using wavelets

Author(s)

Cristiano Marcos Agulhari

• Document type: Master's Dissertation
• Press: Campinas, SP.
• Institution: Universidade Estadual de Campinas (UNICAMP). Faculdade de Engenharia Elétrica e de Computação
• Defense date: 2009-11-02

Examining board members

Ivanil Sebastião Bonatti; Rodrigo Capobianco Guido; Pedro Luis Dias Peres

• Advisor: Ivanil Sebastião Bonatti

Abstract

The main contribution of the present thesis is the proposition of two electrocardiogram (ECG) compression methods. The first method, called Run Length Encoding Adaptativo (RLEA), is based on wavelet transforms and consists of using a wavelet function, obtained by the resolution of an optimization problem, which fits to the signal to be compressed. The optimization problem becomes unconstrained with the parametrization of the coefficients of the scaling filter, that define uniquely a wavelet function. After the resolution of the optimization problem, the wavelet decomposition procedure is applied to the signal and the most significant coefficients of representation are retained, being the number of retained coefficients determined in order to satisfty a pre-specified distortion measure. The retained coefficients are quantized and compressed, likewise the bitmap that informs the positions of the retained coefficients. The quantization is performed in an adaptive way, using different numbers of bits for the different decomposition subspaces considered. Both the values of the retained coefficients and the bitmap are encoded using a modi- fied version of the Run Length Encoding technique. The second method proposed in this dissertation, called Zero Padding Singular Values Decomposition (ZPSVD), consists of detecting the beat pulses of the ECG, equalizing the pulses by inserting zeros (zero padding), and finally applying the SVD to obtain both the basis and the coefficients of representation of the beat pulses. Some components of the basis are retained and then compressed using the same procedures applied to the coefficients of decomposition of the ECG in the RLEA method, while the coefficients of projection of the beat pulses in the basis are quantized using an adaptive quantization procedure. Both proposed compression methods are compared to other techniques by means of numerical experiments (AU)

• FAPESP's process: 06/05170-8 - Signal compression
• Grantee: Cristiano Marcos Agulhari
• Support Opportunities: Scholarships in Brazil - Master