Why the study?
Existing ECG data compression methods do not fully exploit signal characteristics, leading to suboptimal compression for fast data transfer and reduced storage costs.
Does a novel data compression technique combining Savitzky-Golay filtering, DCT, and Huffman coding improve compression ratio and signal fidelity in ECG signals?
Does a novel data compression technique combining Savitzky-Golay filtering, DCT, and Huffman coding improve compression ratio and signal fidelity in ECG signals?
The proposed ECG compression algorithm achieves high compression ratios with minimal signal distortion, potentially facilitating efficient storage and transmission of large volumes of ECG data in healthcare.
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May aid ECG data handling in telemedicine; leaves open prospective clinical validation.
Luanloet et al. (2023) studied this question.
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