@article{oai:niigata-u.repo.nii.ac.jp:00001886,
 author = {Nakashizuka, Makoto and Niwa, Kazuki and Kikuchi, Hisakazu},
 issue = {8},
 journal = {IEICE transactions on fundamentals of electronics, communications and computer sciences, IEICE transactions on fundamentals of electronics, communications and computer sciences},
 month = {Aug},
 note = {In this paper, we propose an ECG waveform compression technique based on the matching pursuit. The matching pursuit is an iterative non-orthogonal signal expansion technique. A signal is decomposed to atoms in a function dictionary. The constraint to the dictionary is only the over-completeness to signals. The function dictionary can be defined to be best match to the structure of the ECG waveform. In this paper, we introduce the multiscale analysis to the implementation of inner product computations between signals and atoms in the matching pursuit iteration. The computational cost can be reduced by utilization of the filter bank of the multiscale analysis. We show the waveform approximation capability of the matching pursuit with multiscale analysis. We show that a simple 4-tap integer filter bank is enough to the approximation and compression of ECG waveforms. In ECG waveform compression, we apply the error feed-back procedure to the matching pursuit iteration to reduce the norm of the approximation error. Finally, actual ECG waveform compression by the proposed method are demonstrated. The proposed method achieve the compression by the factor 10 to 30. The compression ratio given by the proposed method is higher than the orthogonal wavelet transform coding in the range of the reconstruction precision lower than 9% in PRD.},
 pages = {1919--1932},
 title = {ECG Data Compression by Matching Pursuits with Multiscale Atoms},
 volume = {E84-A},
 year = {2001}
}