Optimum wavelet transform-based ECG compression and Dissimilarity Measure Based Noise Performance Analysis

In this study, an optimum wavelet transform-based ECG
compression technique is proposed and its noise
performance analysis is investigated. The major addressed
issue is guaranteeing an error limit as small as possible
measured by the percent root mean square difference
(PRD) for the reconstructed ECG signal at every segment
while keeping the compression ratio (CR) as large as
possible with reasonable implementation complexity. For
this purpose, an optimum wavelet transform-based
compression algorithm is developed. Noise effects on the
normal and the arrhythmia signal is analyzed based on the
compression ratio (CR) and the reconstruction distortion.
The similarity measurement is used as a criterion to
analyze how much the original signal is similar or closer
to the reconstructed one. Two numerical metrics PRD and
CR are used as the major performance evaluation
parameters to analyze the results of the implemented
method quantitatively. Using the developed technique,
different types of orthonormal wavelets are compared.