Electrocardiogram (ECG) signal compression is playing a vital role in biomedical applications. The signal compression is meant for detection and removing the redundant information from the ECG signal. This paper proposes a new technique of ECG compression using Wavelet packet transform methods up to 4th level of decomposition. The quality measurement of the reconstructed signal in an electrocar...

The aim of this study is to show that the measures derived from Electrocardiogram (ECG) signals many a time perform better than the same measures obtained from heart rate (HR) signals. A comparison was made to investigate how far the nonlinear symbolic dynamics approach helps to characterize the nonlinear properties of ECG signals and HR signals, and thereby discriminate between normal and cong...

LetG be a locally compact topological group and EG its universal space for the family of compact subgroups. We give criteria for this space to be G-homotopy equivalent to a d-dimensional G-CW -complex, a finite G-CW -complex or a G-CW -complex of finite type. Essentially we reduce these questions to discrete groups, and to the homological algebra of the orbit category of discrete groups with re...

In this paper novel compression techniques are developed for portable heart-monitoring equipment that could also form the basis for more intelligent diagnostic systems thanks to the way the compression algorithms depend on signal classification. There are two main categories of compression which are employed for electrocardiogram signals: lossless and lossy. Design of an optimal Wiener filter i...