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Evaluation of the shape-varying structuring element in QRS detection for ECG compression

Tadejko P., Rakowski W.

Image Processing & Communications

2005

Vol. 10, no 2

27-38

Morphological operations are simple mathematical constructs, which have led to effective solution for many problems in signal and image processing. These solutions employ discrete operators (structuring element) and are applied to digitized signals. The paper presents the mathematical morphology approach to the recognition and classification of heart rhythms on the basis of electrocardiogram (EGG) waveforms. The main part in recognition is based on the morphological niters characterization of the QRS complexes. In this work, we present morphological filtering as a preliminary step for compression of ECG data using image compression algorithms. To corn-press the ECG data using for example JPEG2000, SPITH or other codec, the one-dimensional ECG sequence needs to be processed to produce a two-dimensional matrix. Detecting operator designed for creating sequence is controlled by the shape and size of the structuring element. We compare how shape and length of this element can affects sensitivity detection algorithm based on amplitude and slope. The performance of the algorithm is evaluated with standard MIT/BIll arrythmia database.

Reducing the spatial signal correlation for the compression of multilead electrocardiographic recordings

Augustyniak P.

Journal of Medical Informatics & Technologies

2001

Vol. 2, Part. 2

MT107--MT115

This paper is devoted to the transform-based method for decorrelation of simultaneously recorded ECG channels. The conventional 12-lead ECG recordings, due to the non-optimal lead positioning, contain highly redundant data. Eliminating this redundancy yields new possibilities for lossless coding of the ECG, meeting the most severe expectations about the quality of stored signal. The statistical properties featured by uncorrelated signals in the transform domain are more appropriate for the data distribution-based coding techniques. In our work four linear transforms are studied and numerically verified with use of the real ECG data. Additionally, the combination of spatial and temporal decorreation is proposed and discussed as the practical and lossless method for a real implementation. The compression efficiency significantly exceeds the values obtained with use of general-purpose lossless algorithms.