METHODS AND DEVICES FOR DISPLAYING TREND AND VARIABILITY IN A PHYSIOLOGICAL DATASET

1 . A method of displaying trends and variability in a physiological dataset, comprising, on a processor:

obtaining the physiological dataset;

applying a smoothing algorithm to the physiological dataset to obtain a trend of the physiological dataset;

applying a variability algorithm to the physiological dataset to obtain the variability of the physiological dataset;

outputting a graph of the trend of the physiological dataset; and

outputting a graph of the variability of the physiological dataset.

2 . The method of claim 1 , wherein the physiological dataset is based on data obtained from a patient's respiratory system.

3 . The method of claim 1 , wherein the smoothing algorithm is one of a moving average algorithm and a digital filter algorithm.

4 . The method of claim 1 , wherein the graph of the trend of the physiological dataset and the graph of the variability of the physiological dataset are one of overlaid and graphed adjacently.

5 . The method of claim 1 , wherein the graph of the variability of the physiological dataset comprises an envelope bounded on the top by a plot of the maximums identified by the variability algorithm and bounded on the bottom by a plot of the minimums identified by the variability algorithm.

6 . The method of claim 5 , wherein the space between the bounds is shaded.

7 . The method of claim 6 , wherein the graph of the variability of the physiological dataset is used to assess and diagnose apnea.

8 . The method of claim 1 , wherein the physiological dataset is interbreath interval data.

9 . The method of claim 1 , wherein the graph of variability of the physiological dataset is a function of fractal scaling coefficients calculated at various time points and over various time windows of the dataset.

10 . The method of claim 1 , wherein the graph of variability of the physiological dataset comprises one or more of, error bars, line graphs, momentum bars, shaded areas under a curve, and a stochastic plot.

11 . The method of claim 1 , wherein the magnitude of the variability which is displayed by the graph of variability of the physiological dataset is calculated as a function of at least one of, the raw dataset, the smoothed dataset, multiple smoothed datasets, the fractal scaling coefficients of the dataset, or the stochastic coefficients of the dataset.

12 . A device comprising:

a transthoracic impedance measurement device to obtain a physiological dataset;

a processor receiving the physiological dataset from the measurement device, and adapted to:

apply a smoothing algorithm to the physiological dataset to obtain a trend of the physiological dataset; and

apply a variability algorithm to the physiological dataset to obtain the variability of the physiological dataset ; and

an output device coupled to the processor and adapted to:

output a graph of the trend of the physiological dataset; and

output a graph of the variability of the physiological dataset.

13 . A system for displaying trends and variability in a physiological dataset, comprising:

a patient monitoring device;

at least one sensor coupled to the patient monitoring device;

a processor contained within the patient monitoring device and receiving patient data from the at least on sensor;

a screen contained within the patient monitoring device and receiving display information from the processor;

wherein the processor:

obtains the physiological dataset from the at least one sensor;

applies a smoothing algorithm to the physiological dataset to obtain a trend of the physiological dataset;

applies a variability algorithm to the physiological dataset to obtain the variability of the physiological dataset;

outputs a graph of the trend of the physiological dataset to the screen; and

outputs a graph of the variability of the physiological dataset to the screen.

14 . The system of claim 13 , wherein the physiological dataset is based on data obtained from a patient's respiratory system.

15 . The system of claim 13 , wherein the smoothing algorithm is one of a moving average algorithm and a digital filter algorithm.

16 . The system of claim 13 , wherein the graph of the trend of the physiological dataset and the graph of the variability of the physiological dataset are one of overlaid and graphed adjacently.

17 . The system of claim 13 , wherein the graph of the variability of the physiological dataset comprises an envelope bounded on the top by a plot of the maximums identified by the variability algorithm and bounded on the bottom by a plot of the minimums identified by the variability algorithm.

18 . The system of claim 17 , wherein the space between the bounds is shaded.

19 . The system of claim 18 , wherein the graph of the variability of the physiological dataset is used to assess and diagnose apnea.

20 . The system of claim 13 , wherein the physiological dataset is interbreath interval data.