Cooperative processing with mobile monitoring device and computer system

1. A mobile device comprising:

circuitry to receive ECG data;

circuitry to identify a notable finding in the ECG data;

circuitry to send the ECG data corresponding to the notable finding to a computing system; and

circuitry to receive from the computing system a pattern based on analysis of the ECG data sent from the computing system using additional computing resources of the computing system.

2. The mobile device of claim 1 wherein circuitry in the mobile device processes signals according to the pattern sent to the mobile device by the computing system.

3. The mobile device of claim 1 wherein circuitry in the mobile device processes data collected by the mobile device according to the pattern sent to the mobile device by the computing system.

4. The mobile device of claim 1 wherein the pattern comprises templates of signal morphologies, additional data, additional processing rules or additional executable computer programs.

5. The mobile device of claim 1 wherein the patterns are produced from historical data on the user, the historical data including ECG strips, or templates or reference data.

6. The mobile device of claim 1 wherein the mobile device operates in standalone mode when access to the computing system is not available, and during that time, saves notable findings and ECG data in non-volatile memory.

7. The mobile device of claim 1 wherein the mobile device is further configured to receive from the computing system at least one pattern to cause the mobile device to process subsequent electrical signals of the beating heart using the pattern.

8. The mobile device of claim 1 wherein criteria are used to determine if a detected episode corresponds to a notable finding; and

wherein the detected episode is determined by detecting that a pattern produced from the data corresponding to the notable finding does not match any patterns stored in the mobile device.

9. The mobile device of claim 1 wherein determining that a detected episode is a notable finding comprises at least one of detecting a high level of noise in the signal and determining that a quality measure related to the notable finding indicates low quality.

10. The mobile device of claim 1 , further comprising sensors to receive physiological signals from a subject;

circuitry that conditions the signals from the sensors and converts the signals to digital data; and

a computing device to process the digital data to produce the notable finding.

11. The mobile device of claim 10 further comprising a storage device that stores a computer program product to cause the mobile device to:

analyze the digital signals representative of a beating heart;

conduct a detailed analysis to determine when the digital data corresponds to a notable finding;

determine when to send the digital data corresponding to the notable finding to a second computing system for re-analysis;

utilize a process to receive a selected new pattern to re-configure the mobile device to change analysis of data received by the mobile device; and

utilize a wireless link that allows the mobile device to communicate with the second computing system.

12. A method of using a mobile device comprising:

receiving ECG data from a mobile device;

identifying a notable finding in the ECG data on the mobile device;

sending the ECG data corresponding to the notable finding from the mobile device to a computing system; and

receiving on the mobile device a pattern based on analysis of the ECG data sent from the computing system using additional computing resources of the computing system.

13. The method of claim 12 further comprising processing signals according to the pattern sent to the mobile device by the computing system.

14. The method of claim 12 further comprising processing data collected by the mobile device according to the pattern sent to the mobile device by the computing system.

15. The method of claim 12 wherein the pattern comprises templates of signal morphologies, additional data, additional processing rules or additional executable computer programs.

16. The method of claim 12 wherein the patterns are produced from historical data on the user, the historical data including ECG strips, or templates or reference data.

17. The method of claim 12 wherein the mobile device operates in standalone mode when access to the computing system is not available, and during that time, saves notable findings and ECG data in non-volatile memory.

18. The method of claim 12 wherein the mobile device is further configured to receive from the computing system at least one pattern to cause the mobile device to process subsequent electrical signals of the beating heart using the pattern.

19. The method of claim 12 wherein criteria are used to determine if a detected episode corresponds to a notable finding;

and wherein the detected episode is determined by detecting that a pattern produced from the data corresponding to the notable finding does not match any pattern stored in the mobile device.

20. The method of claim 12 wherein determining that a detected episode is a notable finding comprises at least one of detecting a high level of noise in the signal and determining that a quality measure related to the notable finding indicates low quality.

21. The method of claim 12 further comprising using sensors to receive physiological signals from a subject;

conditioning signals from the sensors and converting the signals to digital data; and

processing the digital data to produce the notable finding.

22. The method of claim 21 further comprising analyzing the digital signals representative of a beating heart;

conducting a detailed analysis to determine when the digital data corresponds to the notable finding;

determining when to send the digital data corresponding to the notable finding to a second computing system for re-analysis;

receiving a selected new pattern to re-configure the mobile device to change analysis of data received by the mobile device; and

wirelessly communicating with the second computing system.