Patent ID: 8484153
Filing Date: 2013-07-09
Classification: A61B,G06N,G16H,G16Z

Abstract:
1. A system for predicting a circadian state of an individual, the system comprising: a processor connected to receive light stimulus information related to light stimulus to which the individual is exposed; wherein the processor is configured to: provide a model representative of circadian response to the light stimulus information, the model comprising one or more model variables and at least one model variable representative of a probability distribution function (PDF) of a phase offset of the circadian state of the individual; and use the model and the light stimulus information to estimate an updated PDF of the phase offset, wherein using the model and the light stimulus information to estimate the updated PDF of the phase offset comprises performing a Bayesian estimation process commencing with an initial PDF of the phase offset and iterating toward the updated PDF of the phase offset; and wherein the processor is configured to perform the Bayesian estimation process using a particle filtering procedure which comprises: converting the initial PDF into an initial set of discrete particles representative of the initial PDF, each of the initial particles comprising a point; iteratively propagating the initial set of discrete particles through the Bayesian estimation process to obtain an updated set of discrete particles; and converting the updated set of discrete particles into the updated PDF of the phase offset; and wherein the processor is configured to iteratively propagate the initial set of discrete particles through the Bayesian estimation process by, for each iteration: obtaining a first set of discrete particles, the first set of discrete particle comprising one of: the initial set of discrete particles or an output set of discrete particles from a previous iteration; performing a prediction update operation on the first set of discrete particles, the prediction update operation based on application of a state transition equation of the model to the first set of discrete particles and the prediction update operation outputting a second set of discrete particles.