Abstract
The assessment of ECG signal quality after compression is an essential part of the compression process. Compression facilitates the signal archiving, speeds up signal transmission, and reduces the energy consumption. Conversely, lossy compression distorts the signals. Therefore, it is necessary to express the compression performance through both compression efficiency and signal quality. This paper provides an overview of objective algorithms for the assessment of both ECG signal quality after compression and compression efficiency. In this area, there is a lack of standardization, and there is no extensive review as such. 40 methods were tested in terms of their suitability for quality assessment. For this purpose, the whole CSE database was used. The tested signals were compressed using an algorithm based on SPIHT with varying efficiency. As a reference, compressed signals were manually assessed by two experts and classified into three quality groups. Owing to the experts' classification, we determined corresponding ranges of selected quality evaluation methods' values. The suitability of the methods for quality assessment was evaluated based on five criteria. For the assessment of ECG signal quality after compression, we recommend using a combination of these methods: PSim SDNN, QS, SNR1, MSE, PRDN1, MAX, STDERR, and WEDD SWT.
Highlights
The evaluation of the quality of electrocardiogram (ECG) after compression is an essential part of compression in the broadest sense
Subjective methods are based on the assessment of ECG signal quality by cardiologists or other experts and are described in Section 3.1, while objective methods are further divided into the following: methods without diagnostic information, methods with diagnostic information based on wavelet transform (WT), and methods with diagnostic information based on delineation
The performance of various quality measures was compared based on five different criteria: (1) we depicted the average R-D curves for all tested methods; (2) we calculated three features of R-D curves at the important average value length (avL) limit of 0.8 bps: sensitivity, variability, and sensitivity-variability ratio (SVR); (3) we did the cross-correlation analysis to compare the whole trend of the methods while we performed cluster analysis to classify the methods in groups according to their trend similarity; (4) we determined the computational demand of the methods; and (5) we considered the popularity of the methods (Table 1)
Summary
The evaluation of the quality of electrocardiogram (ECG) after compression is an essential part of compression in the broadest sense. Compression usually results in loss of signal quality. This arises in the case of lossy compression, which is the most commonly used technique because of its high efficiency. While the quality of the signal after lossless compression is preserved, the efficiency is low. The aim of compression is to maximize the reduction of data amount while preserving the quality (diagnostic information). This naturally results in a compromise between efficiency and quality. It is desirable to express the compression performance through both efficiency and quality to avoid misunderstanding [1]
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