Title :
Wavelet compression of ECG signals by the set partitioning in hierarchical trees algorithm
Author :
Lu, Zhitao ; Kim, Dong Youn ; Pearlman, William A.
Author_Institution :
Dept. of Electr. Comput. & Syst. Eng., Rensselaer Polytech. Inst., Troy, NY, USA
fDate :
7/1/2000 12:00:00 AM
Abstract :
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 (A. Said and W.A. Pearlman, IEEE Trans. Ccts. Syst. II, vol. 6, p. 243-50, 1996) has achieved notable success in still image coding. The authors 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.
Keywords :
data compression; electrocardiography; medical signal processing; trees (mathematics); wavelet transforms; ECG signals compression; bit stream generation; electrodiagnostics; exact bit rate control; hierarchical trees algorithm; hierarchical trees compression algorithm; portable heart monitoring; progressive bit stream; set partitioning; still image coding; wavelet electrocardiogram data codec; wavelet signal processing; Biomedical engineering; Codecs; Compression algorithms; Electrocardiography; Image coding; Partitioning algorithms; Signal processing; Signal processing algorithms; Signal resolution; Wavelet transforms; Algorithms; Arrhythmias, Cardiac; Biomedical Engineering; Data Interpretation, Statistical; Databases, Factual; Electrocardiography; Humans; Signal Processing, Computer-Assisted;
Journal_Title :
Biomedical Engineering, IEEE Transactions on
