Key result
Wavelet-based ECG compression achieves high compression ratios while maintaining signal fidelity.
Why the study?
Compression of digital ECG signals is desirable to economize storage space and reduce data transmission requirements while preserving signal morphology.
Wavelet-based compression allows for substantial reduction in ECG data size while maintaining signal morphology acceptable for clinical interpretation.
May enable efficient ECG storage and teletransmission; leaves open clinical validation of reconstructed signal fidelity.
Compression of digital Electrocardiogram (ECG) signals is desirable for two reasons: economic use of storage space for databases and reduction of the data for transmission on telephone lines. This paper deals with waveletbased compression method. This method of ECG data compression leads to substantial amount of ECG reduction with less amount of the data loss. The wavelet functions can be used to decompose the ECG signal and upon reconstruction, the signal can be presented without loss of signal morphology. The analysis and synthesis filters play a very important role in this process. The analysis filter decomposes the signal using a pair of low-pass and high-pass filters, whereas the synthesis filter reconstructs the decomposed part. There is a faithful reconstruction on applying the synthesis filter to the ECG signal which is acceptable to the cardiologists. The performance parameters can support the technique of data compression. It is observed that even for higher Compression Ratio (CR) fidelity can be maintained and is verified by Cross-Correlation Coefficient (CCC).
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Kanhe et al. (2014) studied Electrocardiogram (ECG) signals. Wavelet-based compression method was evaluated on Compression Ratio (CR) and Cross-Correlation Coefficient (CCC). Wavelet-based compression of ECG signals achieves high compression ratios while maintaining signal fidelity, as verified by the cross-correlation coefficient.
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