Monitoring patient status through principal components analysis

Principal component (PC) analysis allows the definition of a transform with optimum coefficients. The PCs of several time series of the features, extracted from the electrocardiograms (ECGs) or the arterial pressure, are calculated. With the assumption that the statistical structure of intra-patient data is going to be stable, the basis functions of the transforms are captured once, during a basal interval. A function has been derived from the two first PCs, which represent an evidence function to be used both for a compact visual presentation and for the design of an algorithm for automatic episode detection. The evaluation of the visual presentation has been based on the annotated signal of the European ST-T database.<<ETX>>