Title :
A comparative study of adaptive algorithms for ECG data compression using Hermite models
Author :
Jané, Raimon ; Olmos, Salvador
Author_Institution :
Inst. de Cibernetica, CSIC, Barcelona, Spain
Abstract :
Modeling of signals using Hermite functions is a very appropriate technique for ECG data compression. ECG signal can be highly nonstationary in ambulatory monitoring or during stress test. Adaptive algorithms with a fast convergence are necessary, when data compression of nonstationary signals must be performed. Here, the authors analyse several adaptive algorithms that improves the behaviour of classical least mean squares
Keywords :
data compression; ECG data compression; Hermite models; adaptive algorithms comparison; ambulatory monitoring; classical least mean squares; fast convergence algorithms; highly nonstationary signal; stress test; Adaptive algorithm; Algorithm design and analysis; Approximation algorithms; Convergence; Data compression; Electrocardiography; Least squares approximation; Parameter estimation; Stress; Testing;
Conference_Titel :
Engineering in Medicine and Biology Society, 1994. Engineering Advances: New Opportunities for Biomedical Engineers. Proceedings of the 16th Annual International Conference of the IEEE
Conference_Location :
Baltimore, MD
Print_ISBN :
0-7803-2050-6
DOI :
10.1109/IEMBS.1994.415423
