A low computational complexity algorithm for ECG signal compression.
In this work, a filter bank-based algorithm for electrocardiogram (ECG) signals compression is proposed. The new coder consists of three different stages. In the first one--the subband decomposition stage--we compare the performance of a nearly perfect reconstruction (N-PR) cosine-modulated filter bank with the wavelet packet (WP) technique. Both schemes use the same coding algorithm, thus permitting an effective comparison. The target of the comparison is the quality of the reconstructed signal, which must remain within predetermined accuracy limits. We employ the most widely used quality criterion for the compressed ECG: the percentage root-mean-square difference (PRD). It is complemented by means of the maximum amplitude error (MAX). The tests have been done for the 12 principal cardiac leads, and the amount of compression is evaluated by means of the mean number of bits per sample (MBPS) and the compression ratio (CR). The implementation cost for both the filter bank and the WP technique has also been studied. The results show that the N-PR cosine-modulated filter bank method outperforms the WP technique in both quality and efficiency.
Dep. Teoría de la Señal y Comunicaciones, Escuela Politécnica, Universidad de Alcalá, Alcalá de Henares, Madrid, Spain. manuel.blanco@uah.es
Manuel
M
Blanco-Velasco
Fernando
F
Cruz-Roldán
Francisco
F
López-Ferreras
Angel
A
Bravo-Santos
Damián
D
Martínez-Muñoz
D000465:Algorithms; D001698:Biomedical Engineering; D003627:Data Interpretation, Statistical; D004562:Electrocardiography; D008955:Models, Cardiovascular; D012815:Signal Processing, Computer-Assisted; D013997:Time Factors