Key result
An ECG data compression scheme using gain-shape vector quantization achieved an average PRD of 5.97% at 127 b/s across 48 records in the MIT-BIH database.
The proposed gain-shape vector quantization method for ECG compression achieves excellent visual and objective quality at low bit rates.
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Offers viable low-bitrate ECG compression; leaves open prospective clinical validation and workflow integration.
An electrocardiogram (ECG) data compression scheme is presented using the gain-shape vector quantization. The proposed approach utilizes the fact that ECG signals generally show redundancy among adjacent heartbeats and adjacent samples. An ECG signal is QRS detected and segmented according to the detected fiducial points. The segmented heartbeats are vector quantized, and the residual signals are calculated and encoded using the AREA algorithm. The experimental results show that with the proposed method both visual quality and the objective quality are excellent even in low bit rates. An average PRD of 5.97% at 127 b/s is obtained for the entire 48 records in the MIT-BIH database. The proposed method also outperforms others for the same test dataset.
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Sun et al. (2005) studied ECG signals (n=48). Gain-shape vector quantization for ECG data compression vs. Other compression methods was evaluated on Average PRD (Percentage Root-mean-square Difference) at 127 b/s. An ECG data compression scheme using gain-shape vector quantization achieved an average PRD of 5.97% at 127 b/s across 48 records in the MIT-BIH database.
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