Simultaneous Optimized Orthogonal Matching Pursuit with Application to ECG Compression

TL;DR

This paper introduces a greedy pursuit strategy called Simultaneous Optimized Orthogonal Matching Pursuit that finds a common basis for approximating multiple similar signals, improving ECG compression efficiency.

Contribution

It extends the OOMP approach to jointly select subspaces for multiple signals, optimizing mean error norm at each step for better compression.

Findings

Significant gains in ECG compression over existing methods

Effective joint basis selection for similar signals

Improved approximation accuracy on MIT-BIH dataset

Abstract

A greedy pursuit strategy which finds a common basis for approximating a set of similar signals is proposed. The strategy extends the Optimized Orthogonal Matching Pursuit approach to selecting the subspace containing the approximation of all the signals in the set. The method, called Simultaneous Optimized Orthogonal Matching Pursuit, is stepwise optimal in the sense of minimizing at each iteration the mean error norm of the joint approximation. When applied to compression of electrocardiograms, significant gains over other transformation based compression techniques are demonstrated on the MIT-BIH Arrhythmia dataset.