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A novel ECG data compression method based on adaptive Fourier decomposition
Tan C.; Zhang L.
2017
Source PublicationProceedings of SPIE - The International Society for Optical Engineering
Volume10613
AbstractThis paper presents a novel electrocardiogram (ECG) compression method based on adaptive Fourier decomposition (AFD). AFD is a newly developed signal decomposition approach, which can decompose a signal with fast convergence, and hence reconstruct ECG signals with high fidelity. Unlike most of the high performance algorithms, our method does not make use of any preprocessing operation before compression. Huffman coding is employed for further compression. Validated with 48 ECG recordings of MIT-BIH arrhythmia database, the proposed method achieves the compression ratio (CR) of 35.53 and the percentage root mean square difference (PRD) of 1.47% on average with N = 8 decomposition times and a robust PRD-CR relationship. The results demonstrate that the proposed method has a good performance compared with the state-of-the-art ECG compressors.
KeywordAdaptive Fourier decomposition (AFD) Biomedical signal processing Data compression e-health Electrocardiogram (ECG)
DOI10.1117/12.2299967
URLView the original
Language英語
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Cited Times [WOS]:0   [WOS Record]     [Related Records in WOS]
Document TypeConference paper
CollectionUniversity of Macau
AffiliationUniversidade de Macau
Recommended Citation
GB/T 7714
Tan C.,Zhang L.. A novel ECG data compression method based on adaptive Fourier decomposition[C],2017.
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