CARDIAC MONITORING DEVICE AND METHOD

• US 20160106330A1
• Filed: 10/16/2015
• Published: 04/21/2016
• Est. Priority Date: 10/17/2014
• Status: Abandoned Application

• Current Assignee: ECM Foresights LLC
• Original Assignee: ECM Foresights LLC
• Inventors: Abernethy, Matthew C., Dotani, Mohammad I., Prakash, Amit
• Application Number:
  US14/885,384
• Publication Number:
  US 20160106330A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: A61B 2562/085 combined with means for recording calibration data
• CPC Class Codes: A61B 5/0006 ECG or EEG signals
• CPC Class Codes: A61B 5/303 Patient cord assembly, e.g. cable harness
• CPC Class Codes: A61B 5/349 Detecting specific parameters of the electrocardiograph cycle
• CPC Class Codes: A61B 5/4836 Diagnosis combined with treatment in closed-loop systems or methods A61B5/0036 takes precedence
• CPC Class Codes: A61B 5/6823 Trunk, e.g., chest, back, abdomen, hip
• CPC Class Codes: A61B 5/686 Permanently implanted devices, e.g. pacemakers, other stimulators, biochips A61B5/6861 takes precedence
• CPC Class Codes: A61B 5/6898 Portable consumer electronic devices, e.g. music players, telephones, tablet computers
• CPC Class Codes: A61B 5/7275 Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor
• CPC Class Codes: A61B 5/7282 Event detection, e.g. detecting unique waveforms indicative of a medical condition A61B5/4094, A61B5/4818, A61B5/349, A61B5/0823 take precedence
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 40/67 for remote operation
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/50 for simulation or modelling of medical disorders

Abstract

A method of predicting cardiac disease includes the steps of: attaching a monitoring device to a patient; obtaining cardiac information from the patient using the monitoring device; transmitting the obtained cardiac information from the monitoring device to a data-computing device; analyzing the transmitted cardiac information using the data-computing device and a predictive model; building an indication report from the analyzed cardiac information; and outputting the indication report.

Claims

1. A method of predicting cardiac disease, comprising the steps of:

attaching a monitoring device to a patient;

obtaining cardiac information from the patient using said monitoring device;

transmitting said obtained cardiac information from said monitoring device to a data-computing device;

analyzing said transmitted cardiac information using said data-computing device and a predictive model;

building an indication report from said analyzed cardiac information; and

outputting said indication report.

2. The method according to claim 1, wherein said analyzing step comprises:

storing baseline data in at least one of a local and remote data center utilized by said data-computing device;

comparing said transmitted cardiac information to said baseline data; and

determining a predictive score based on said comparison.

3. The method according to claim 2, further comprising the step of outputting an alerting signal from said data center to an alerting device based on said predictive score.

4. The method according to claim 2, further comprising the step of outputting a treatment signal from said data center to a treatment device based on said predictive score.

5. The method according to claim 4, wherein said treatment device is at least one of a pacemaker, a defibrillator, and a medication pump.

6. The method according to claim 4, wherein said treatment device is connected to said monitoring device.

7. The method according to claim 6, wherein said cardiac event is at least one of a myocardial infarction, a stroke, an atrial fibrillation, an aortic aneurism, and an aortic dissection.

8. The method according to claim 2, further comprising the steps of:

storing said transmitted cardiac information as a patient cardiac state;

determining if a cardiac event has occurred in a stored time interval following storing said patient cardiac state; and

adding said cardiac event determination and said patient cardiac state to said baseline data.

9. The method according to claim 8, further comprising the step of associating said patient cardiac state with an occurred cardiac event prior to adding said cardiac event determination and said patient cardiac state to said baseline data.

10. The method according to claim 1, wherein said indication report is output to at least one of said monitoring device, a web environment, a memory unit, and said data-computing device.

11. The method according to claim 1, wherein said obtained cardiac information includes at least one of a length of a P wave, a height of a P wave, a length of a P-R interval, a height of a P-R interval, a QRS wave width, a QRS wave height, a QRS wave shape, an S-T interval, an S-T height, a T wave height, a T wave length, a Q-T length, a QTc, a T-P interval, a slope change of a QRS wave in a predetermined period of a heart ventricle polarization, a T wave shape change, and a P wave shape change.

12. The method according to claim 1, wherein said transmitting, analyzing, and outputting steps occur at predetermined time intervals.

13. The method according to claim 1, wherein said analyzing step includes using an algorithm to determine cardiac event indicators.

14. The method according to claim 13, wherein said algorithm is modified by subsequently transmitted cardiac information.

15. A method of maintaining a cardiac disease data repository, comprising the steps of:

storing baseline data in a server including at least one memory unit, said baseline data including a plurality of patient cardiac states and a cardiac event indicator associated with at least one of said patient cardiac states;

receiving an incoming patient cardiac state from a monitoring device attached to a patient, said server receiving said incoming patient cardiac state;

receiving an incoming cardiac event indicator associated with said incoming patient cardiac state, said server receiving said incoming cardiac event indicator; and

updating said baseline data to store said incoming patient cardiac state and said associated cardiac event indicator in said at least one memory unit.

16. The method according to claim 15, wherein said incoming cardiac event indicator associated with said incoming patient cardiac state is measured by said monitoring device simultaneously with said incoming patient cardiac state.

17. The method according to claim 15, further comprising the step of determining overlap between said received incoming patient cardiac state and patient cardiac states with similar cardiac event indicators stored in said baseline data.

18. The method according to claim 17, wherein said determined overlap is stored in said at least one memory unit as an event risk indicator.

19. The method according to claim 15, wherein said incoming cardiac event indicator associated with said incoming patient cardiac state is measured by said monitoring device within a predetermined monitoring interval of said incoming patient cardiac state.