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Abstract

A method and apparatus for monitoring the status of a patient on the basis of a plurality of vital signs measurements such as heart rate, breathing rate, blood pressure, temperature, oxygen saturation etc. At each time point a set of such vital signs measurements is compared to two statistical models, one being a population-based statistical model representing the probability distribution of measurements from a large number of individuals, and the second is a patient-specific statistical model based on measurements from the particular patient being monitored. The patient-based statistical model is initialized as identical to the population-based model, but then is updated in a Bayesian update technique so that it evolves towards the patient's individual state. First and second novelty indexes are calculated by comparing each status measurement to each of the two statistical models. A threshold on the novelty index from the population-based model can generate an alarm if the index indicates that the patient's status is outside a predefined normal region for the population. A threshold on the numerical index from the patient-specific model can indicate a change in status of the patient, which can be an improvement or a deterioration.

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