Cardiogram Analysis and Classification Using Signal Analysis Techniques.
Rough draft 1 Sep 73-31 Aug 74,
CHARLES STARK DRAPER LAB INC CAMBRIDGE MASS
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The study pertains to the development of automated techniques for classification of vectorcardiograms and electrocardiograms using signal analysis techniques. A data preprocessor is developed to produce an average heartbeat from a record containing multiple heartbeats corrupted by severe baseline shifts. Several techniques for generating an ECGVCG transformation are studied. Individual transformations are found to be quite accurate, if phase shifts among the leads are taken into account. However, patient variability appears to preclude use of a standardized transformation. The structure of the data base required to accurately test the classification algorithms is discussed and specific recommendations are made. The effect of using both two- and three-dimensional coordinate systems and a normalizing transformation for feature generation was studied classification accuracy remained essentially unchanged.
- Medicine and Medical Research