Assessment of ECG Signal Quality After Compression

Assessment of ECG Signal Quality After Compression

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Highly efficient lossy compression algorithms for ECG signals are connected with distortion of the signals; lossy compression is a compromise between compression efficiency and signal quality. It is recommended to express this relation using rate-distortion curve. To decide whether the signal is suitable for further analysis, it is necessary to assess its quality after reconstruction. Although there exist many methods for quality assessment, neither of them is standardized or unified. The methods usually do not offer any information about their acceptable values. This paper introduces 10 new methods for signal quality assessment and their limits. Four methods are simple (entropy, mean, median, spectra similarity), two are based on delineation of ECG (SiP, SiPA), and four combine dynamic time warping, delineation, and calculation of distance (DTWdist, DTWpmfp1, DTWpmfp2, pmfp). These methods are tested on the whole standard CSE database using compression algorithm based on wavelet transform and set partitioning in hierarchical trees. The signals were compressed with various efficiency expressed by average value length (avL). Two ECG experts divided the compressed signals into three quality groups: perfect quality, good quality, not evaluable ECG. Owing to the experts’ ECG classification, we set the range of avL for each quality group. Based on this, we determined corresponding ranges of new methods’ values. Based on the trend of rate-distortion curve, its sensitivity, variability, their ratio at important boundary avL = 0.8 bps, and computational demand of the methods, we recommend four methods for further use.

Highly efficient lossy compression algorithms for ECG signals are connected with distortion of the signals; lossy compression is a compromise between compression efficiency and signal quality. It is recommended to express this relation using rate-distortion curve. To decide whether the signal is suitable for further analysis, it is necessary to assess its quality after reconstruction. Although there exist many methods for quality assessment, neither of them is standardized or unified. The methods usually do not offer any information about their acceptable values. This paper introduces 10 new methods for signal quality assessment and their limits. Four methods are simple (entropy, mean, median, spectra similarity), two are based on delineation of ECG (SiP, SiPA), and four combine dynamic time warping, delineation, and calculation of distance (DTWdist, DTWpmfp1, DTWpmfp2, pmfp). These methods are tested on the whole standard CSE database using compression algorithm based on wavelet transform and set partitioning in hierarchical trees. The signals were compressed with various efficiency expressed by average value length (avL). Two ECG experts divided the compressed signals into three quality groups: perfect quality, good quality, not evaluable ECG. Owing to the experts’ ECG classification, we set the range of avL for each quality group. Based on this, we determined corresponding ranges of new methods’ values. Based on the trend of rate-distortion curve, its sensitivity, variability, their ratio at important boundary avL = 0.8 bps, and computational demand of the methods, we recommend four methods for further use.

Compression;ECG;Electrocardiogram;Quality assessment;Quality evaluation;SPIHT;CSE;database

Compression;ECG;Electrocardiogram;Quality assessment;Quality evaluation;SPIHT;CSE;database

NĚMCOVÁ, A.; VÍTEK, M.; MARŠÁNOVÁ, L.; SMÍŠEK, R.; SMITAL, L.

2019

14.05.2018

Springer Singapore

Praha

978-981-10-9038-7

World Congress on Medical Physics and Biomedical Engineering 2018

IFMBE Proceedings

1680-0737

IFMBE Proceedings

68

3

Francouzská republika

1

5

5

https://www.springer.com/us/book/9789811090226