Several statistical classification techniques were applied to orthogonal electrocardiographic record samples, obtained from normal subjects and patients with left ventricular hypertrophy. A simple method based on addition of QRS amplitude measurements was used as representative of ECG analysis methods in present clinical use. The procedures to be evaluated and compared consisted of vector differences with and without weight factors, and a ciassseparating and a class-clustering transformation.
They were tested both with sets of three and eight amplitude measurements of the QRS complex by using different record samples of 100 each. Best results were obtained with weighted vector differences based on eight amplitudes (84% correct classifications). The class-separating procedure followed with 80%. The conventional method of summing amplitudes led to 67% separation. When amplitude measurements were decreased from eight to three, the differentiation of records deteriorated by 510%.
From the results it was concluded that improvement of ECG record classification can be achieved mainly through increase in number of measurements. More complex statistical classification methods lead only to modest improvements with small numbers of measurements but to a substantial enhancement when more measurements become available. These results indicate a need for automatic means for ECG data analysis because larger numbers of ECG measurements and more efficient classification methods are not practical without access to computer facilities.
Classification of records into various diagnostic categories has always been the main goal in electrocardiography.
In conventional scalar electrocardiography tracings are interpreted and classified on the basis of a limited number of criteria which are derived from the polarity and amplitude of P, Q, R, S, and T waves. Spatial measurements were added with the introduction of vectorcardiography, Both scalar and spatial display methods proved, however, to have inherent limitations for data analysis .I The common practice to select only a few measurements or criteria for diagnostic ECG classification is due * Supported in part by PHS research grants from the National Heart Institute and the Division of Chronic Diseases (CD 00064-06).