DETECTION AND QUANTIFICATION SYSTEM FOR MONITORING INSTRUMENTS

• US 20080183433A1
• Filed: 01/30/2007
• Published: 07/31/2008
• Est. Priority Date: 01/30/2007
• Status: Active Grant

• Current Assignee: Lawrence Livermore National Security LLC (Government of the United States of America)
• Original Assignee: Regents of the University of California (University of California)
• Inventors: Henderer, Bruce D., Hertzog, Claudia K., Dzenitis, John M., Riot, Vincent J., Makarewicz, Anthony J.
• Granted Patent: US 7,412,356 B1
• Time in Patent Office: Days
• US Class Current: 702/193
• CPC Class Codes: G16H 50/80 for detecting, monitoring or modelling epidemics or pandemics, e.g. flu

Abstract

A method of detecting real events by obtaining a set of recent signal results, calculating measures of the noise or variation based on the set of recent signal results, calculating an expected baseline value based on the set of recent signal results, determining sample deviation, calculating an allowable deviation by multiplying the sample deviation by a threshold factor, setting an alarm threshold from the baseline value plus or minus the allowable deviation, and determining whether the signal results exceed the alarm threshold.

Claims

1. A method of detecting real events using a detector that produces signal results at regular intervals, the method distinguishing the real events from noise or variation over time, comprising the steps of:

obtaining a set of recent signal results representing the real events,

calculating measures of the noise or variation based on said set of recent signal results,

calculating an expected baseline value based on said set of recent signal results,

determining sample deviation of said recent signal results,

calculating an allowable deviation by multiplying said sample deviation by a threshold factor,

setting an alarm threshold from said baseline value plus or minus said allowable deviation, and

determining whether the signal results exceed said alarm threshold.

2. The method of detecting real events of claim 1 wherein said step of calculating an expected baseline value comprises calculating said baseline value as the arithmetic mean of said set of recent signal results.

3. The method of detecting real events of claim 1 wherein said step of calculating an expected baseline value includes minimize estimation error by using a covariance matrix of the noise, effectively weighting the recent signal results by their variances.

4. The method of detecting real events of claim 1 wherein said step of obtaining a set of recent signal results comprises including a current data point.

5. The method of detecting real events of claim 1 wherein said step of obtaining a set of recent signal results comprises omitting a current data point.

7. The method of detecting real events of claim 1 wherein said step of determining sample deviation includes the current data point in consideration.

8. The method of detecting real events of claim 1 wherein said step of determining sample deviation omits the current data point in consideration.

9. The method of detecting real events of claim 1 wherein said step of calculating an expected baseline value comprises minimizing estimation error by using a covariance matrix of the noise, effectively weighting the recent signal results by their variances, and the sample deviation is the standard deviation of the recent signal results.

10. The method of detecting real events of claim 1 wherein said step of setting an alarm threshold comprises setting an upper and a lower alarm threshold from said baseline value plus or minus said allowable deviation.

6. (canceled)

11. A computer-implemented method of detecting real events using a detector that produces signal results at regular intervals, the method distinguishing the real events from noise or variation over time, comprising the steps of:

(a) obtaining a set of recent signal results representing the real events,

(b) calculating measures of the noise or variation based on said set of recent signal results,

(c) calculating an expected baseline value based on said set of recent signal results,

(d) determining sample deviation of said recent signal results,

(e) calculating an allowable deviation by multiplying said sample deviation by a threshold factor,

(f) setting an alarm threshold from said baseline value plus or minus said allowable deviation, and

(g) determining whether the signal results exceed said alarm threshold.

12. The method of detecting real events of claim 11 wherein said step of calculating an expected baseline value comprises calculating said baseline value as the arithmetic mean of said set of recent signal results.

13. The method of detecting real events of claim 11 wherein said step of calculating an expected baseline value includes minimize estimation error by using a covariance matrix of the noise, effectively weighting the recent signal results by their variances.

14. The method of detecting real events of claim 11 wherein said step of obtaining a set of recent signal results comprises including a current data point.

15. The method of detecting real events of claim 11 wherein said step of obtaining a set of recent signal results comprises omitting a current data point.

17. The method of detecting real events of claim 11 wherein said step of determining sample deviation includes the current data point in consideration.

18. The method of detecting real events of claim 11 wherein said step of determining sample deviation omits the current data point in consideration.

19. The method of detecting real events of claim 11 wherein said step of calculating an expected baseline value comprises minimizing estimation error by using a covariance matrix of the noise, effectively weighting the recent signal results by their variances, and the sample deviation is the standard deviation of the recent signal results.

20. The method of detecting real events of claim 11 wherein said step of setting an alarm threshold comprises setting an upper and a lower alarm threshold from said baseline value plus or minus said allowable deviation.

16. (canceled)