Wavelet compression of ECG signals by the set partitioning in hierarchical trees algorithm.
A wavelet electrocardiogram (ECG) data codec based on the set partitioning in hierarchical trees (SPIHT) compression algorithm is proposed in this paper. The SPIHT algorithm [1] has achieved notable success in still image coding. We modified the algorithm for the one-dimensional case and applied it to compression of ECG data. Experiments on selected records from the MIT-BIH arrhythmia database revealed that the proposed codec is significantly more efficient in compression and in computation than previously proposed ECG compression schemes. The coder also attains exact bit rate control and generates a bit stream progressive in quality or rate.
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Electrical, Computer, and Systems Engineering Department, Rensselaer Polytechnic Institute, Troy, NY 12180-3590, USA.
Kim
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Pearlman
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WA
D000465:Algorithms; D001145:Arrhythmias, Cardiac / Q000503:physiopathology; D001698:Biomedical Engineering; D003627:Data Interpretation, Statistical; D016208:Databases, Factual; D004562:Electrocardiography / Q000706:statistics & numerical data*; D006801:Humans; D012815:Signal Processing, Computer-Assisted