ABSTRACT
A discriminating program was developed on the basis of time, dynamic and simply calculated parameters of non-invasive tracings recorded in the supine position. Data were derived from ECG, PCG and the indirect carotid pulse curve. The optimal program, formed after 40 experimental processes, was in 85% agreement with the clinical diagnosis. To improve the decision process, we created a new 'test again' group, in addition to the healthy and sick groups. The 'test again' group included 16.5% of the examined subjects. At the same time, there was 75.6% agreement with the clinical diagnosis, and 7.9% disagreement. The risk factors, which could be demonstrated as part of the 'errors' called attention to undetected heart failure. The descriminating function found to be best, was fed into a small computer (R-10). Records for evaluation were entered on magnetic tape to the computer which measured automatically the necessary parameters and printed out the 'decision': 'healthy', 'test again!', or 'cardiac patient', as well as other data, such as systolic time intervals, etc. There is a wide potential application for automated computer system based on non-invasive parameters.