Body surface potential maps classification by center of mass loci

Body surface-potential mapping (BSPM) is used to improve the spatial resolution of measurements of bioelectrical information originating from myocardial sources. Here, a method for data compression is used to define a quantitative parameter which is further used for classification. A sequence of annuli is created from the maps by data compression. A second step extracts the center of mass of each annulus to create a locus assumed to represent the activation process. The Fisher linear discriminant is then used to discriminate between maps which reflect normal and abnormal activity of the heart. Data are recorded over a single heart beat from 25 normal subjects, 17 patients with CAD (coronary artery disease), and 11 patients with WPW (Wolff-Parkinson-White) syndrome. The loci of the centers of mass in 3-D space have been found to be similar within each category and different among the categories. This parameter has successfully categorized 100% of the WPW patients, 94.2% of the CAD diseases, and 80% of the normal subjects. Thus, the parameter extracted from the annuli has been found to be valuable for separation among the various groups.<
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