A study of systolic time intervals during uninterrupted exercise.

A method has been developed for obtaining measurements of the systolic time intervals during uninterrupted graded exercise in the upright position on a bicycle ergometer. The method has been applied to 112 subjects divided into 4 groups: two of normal subjects below and above the age of 40, respectively (mean ages 30 and 48 years), and two of patients (mean ages for each about 50 years), both with coronary insufficiency, but one without and the other with abnormality of left ventricular function as shown by ventriculography. The measurements obtained yield linear relations between total electromechanical systole (QS2) and heart rate, between pre-ejection period (PEP) and RR interval for each subject. The average standard deviation about the regression is less than 6 ms for all three regression lines; the average correlation coefficient is greater than 0-93. The younger group of normal subjects have a significantly shorter PEP compared to the older group. Indices have been derived which separate the patient groups from each other and from the normal subjects. Using these indices 86 per cent of all the subjects were correctly classified according to the group to which they belonged. It is concluded that measurements of STI during uninterrupted exercise offer valuable information in the assessment of cardiac patients.

Automatic determination of systolic time intervals.

Systolic time intervals (STI), measured non-invasively and during uninterrupted exercise, may contain information about cardiac function. A processing system was developed, which determines STI automatically from 8-sec recordings at each load level. A preprocessing unit provides automatic recording and optimal signal-to-noise ratios. One of the main tasks of the computer program, which is modular in structure and written in FORTRAN IV, is to recognize disturbances and artefacts in the signals. After selection of the complexes, usually with some kind of correlation method, a representative beat is found and the inclination points are localized. Besides these points, indicateions of possible errors are given. Preliminary results indicate that the system may be able to replace the human observer in estimating STI.