Patent Document ID: 20150347704
Application ID: 14727696
Patent Flag: 0

Claim One:
1. A method of risk-based monitoring of a critical care patient, the method comprising: providing a plurality of sensors including at least a heart rate sensor and an SpO2 sensor, the plurality of sensors being configured to be physically attachable with the critical care patient; attaching the plurality of sensors to the patient; substantially continuously acquiring, by a computer, physiological data from the plurality of sensors connected with the patient; substantially continuously estimating a clinical trajectory for the patient, the patient's clinical trajectory being described by probabilities of possible patient states using data acquired at a subsequent time step t k+1 from at least the heart rate sensor and the SpO2 sensor attached to the patient, and posterior predicted probability density functions from a previous time step t k , by: generating, by the computer, predicted probability density functions of internal state variables for the time step t k+1 , each of the internal state variables describing a parameter physiologically relevant to at least one of a treatment and a condition of said patient at time step t k+1 , wherein the predicated probability density functions are calculated using posterior estimated probability density functions for each of the internal state variables from a preceding time step t k ; generating, with the computer and using Bayes theorem, posterior predicted probability density functions for the plurality of the internal state variables for the time step t k+1 at least by computing the conditional probability density functions of the data acquired at a time step t k+1 given the internal state variables and the predicated probability density functions of internal state variables; and identifying, with the computer, from the generated posterior predicted probability density functions of the internal state variables at time step t k+1 , into which of a first plurality of possible patient states the patient is currently categorizable; generating a probability value associated with each identified possible patient state; and substantially continuously displaying a clinical trajectory of the patient on a graphical user interface, the user interface being configured to display the probabilities of possible patient states as function of a plurality of time steps.