Investigation of the Behaviour of the Autonomic Nervous System under Stress

of changes that take place in the HF ECG pattern with exercise in the single individual. A not dissimilar scheme can be applied clinically to detect presumed alterations in the myocardial state of the acute cardiac patient. By signal processing of the HF ECG, sufficient noise-reduction can be achieved to produce useful records in nearly all circumstances (even, in diagnostic testing, under exercise conditions). The new patterns are complex, but if the values of the HF ECG waveform are recorded in ranked sequence, a simple quantitative description of the sequence will characterize any changes in waveform as the patient recovers or deteriorates; hence a quantitative trend detection and evaluation procedure does exist. The interesting fact that the procedure now clearly warrants trial in exercisetesting for early coronary ischoemia is an illustration of the basic point that experience in computer processing of clinical signals may prove valuable in devising sensitive methods of health testing for early disease. So this second kind of computer-based signal manipulation leads back to the starting point of this Address. There are interesting and strategically important things to be done with the computer on the clinical signal; often these seek answers to specific questions about the individual patient, but underlying a significant number of these measurements is an attempt to look beyond the variable to the control system influencing it. Knowing about the state of the relevant control system in the body is an important first step to being able to manipulate it. In the meantime, while one cannot negotiate with a body control system, at least one can co-operate with it.