Sensor fusion and probabilistic parameter estimation method and apparatus
View Patent ↗A probabilistic digital signal processor using data from multiple instruments is described. Initial probability distribution functions are input to a dynamic state-space model, which operates on state and/or model probability distribution functions to generate a prior probability distribution function, which is input to a probabilistic updater. The probabilistic updater integrates sensor data from multiple instruments with the prior to generate a posterior probability distribution function passed (1) to a probabilistic sampler, which estimates one or more parameters using the posterior, which is output or re-sampled in an iterative algorithm or (2) iteratively to the dynamic state-space model. For example, the probabilistic processor operates on fused data using a physical model, where the data originates from a mechanical system or a medical meter or instrument, such as an electrocardiogram or pulse oximeter to generate new parameter information and/or enhanced parameter information.
1. A method for processing sensor data representative of a body, comprising the steps of:
using a physical model, representative of function of a body constituent, coded into a digital signal processor of an analyzer, wherein said physical model comprises the step of:
using a fitting constant related to at least one of age and gender;
generating a prior probability distribution function using said physical model;
repetitively fusing input data originating from at least a first medical instrument and a second medical instrument with the prior probability distribution function to generate a posterior probability distribution function; and
processing the posterior probability distribution function with said processor to generate an output of least one of:
a heart attack prediction; and
a heart stroke volume, wherein said step of processing uses at least one equation relating heart stroke volume to the posterior probability distribution function.
2. The method of claim 1 , further comprising the steps of:
determining a noise artifact event through analysis of the input data from said first instrument; and
using said noise artifact event to filter the input data from said second instrument.
3. The method of claim 1 , wherein said estimated parameter value comprises:
a metric to a parameter not output by either said first instrument or said second instrument.
4. The method of claim 3 , wherein said metric comprises a permittivity.
5. The method of claim 1 , wherein the input data from said first instrument comprises hemodynamic data outside of a heart of the body.
6. The method of claim 5 , wherein the input data from said second instrument comprises electrodynamic data representative of an electrodynamic signal originating in the heart of the body.
7. The method of claim 6 , further comprising the step of:
using both the hemodynamic data and the electrodynamic signal to generate an estimate of the autonomic nervous system tone.
8. The method of claim 2 , further comprising the step of:
combining the input signal from said first instrument and said second instrument, said step of combining resulting in at least one of:
a generated measure of heart rate; and
a heart rate variability measure,
wherein the input data from said first instrument comprises a hemodynamic measure.