Clinical decision-support for diagnosing stress-related disorders by applying psychophysiological medical knowledge to an instance-based learning system

摘要

ObjectiveAn important procedure in diagnosing stress-related disorders caused by dysfunction in the interaction of the heart with breathing, i.e., respiratory sinus arrhythmia (RSA), is to analyse the breathing first and then the heart rate. Analysing these measurements is a time-consuming task for the diagnosing clinician. A decision-support system in this area would reduce the analysis task of the clinician and enable him/her to give more attention to the patient. We have created a decision-support system which contains a signal classifier and a pattern identifier. The system performs an analysis of the physiological time series concerned which would otherwise be performed manually by the clinician.