Systems and methods for processing ECG data

• US 9,968,274 B2
• Filed: 04/29/2016
• Issued: 05/15/2018
• Est. Priority Date: 04/29/2016
• Status: Active Grant

• Current Assignee: Infobionic, Inc.
• Original Assignee: Infobionic, Inc.
• Inventors: Korzinov, Lev, Baumann, Eric, McNamara, Anna
• Primary Examiner(s): CAREY, MICHAEL JAMES
• Application Number:
  US15/143,016
• Publication Number:
  US 20170311830A1
• Time in Patent Office: 746 Days
• Field of Search: 607 9, 607 25, 607 27, 600508, 600509, 600515, 600516, 600517, 600518
• CPC Class Codes: A61B 2560/0431 Portable apparatus, e.g. comprising a handle or case
• CPC Class Codes: A61B 5/0006 ECG or EEG signals
• CPC Class Codes: A61B 5/0022 Monitoring a patient using a global network, e.g. telephone networks, internet
• CPC Class Codes: A61B 5/02405 Determining heart rate variability
• CPC Class Codes: A61B 5/02438 with portable devices, e.g. worn by the patient
• CPC Class Codes: A61B 5/25 Bioelectric electrodes therefor
• CPC Class Codes: A61B 5/282 Holders for multiple electrodes for introduction into the body A61B5/287
• CPC Class Codes: A61B 5/316 Modalities, i.e. specific diagnostic methods
• CPC Class Codes: A61B 5/364 Detecting abnormal ECG interval, e.g. extrasystoles, ectopic heartbeats
• CPC Class Codes: A61B 5/6801 specially adapted to be attached to or worn on the body surface
• CPC Class Codes: A61B 5/7203 for noise prevention, reduction or removal
• CPC Class Codes: A61B 5/7246 using correlation, e.g. template matching or determination of similarity
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00
• 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: A61B 5/7475 User input or interface means, e.g. keyboard, pointing device, joystick
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: H04B 1/385 Transceivers carried on the body, e.g. in helmets
• CPC Class Codes: H04L 43/04 Processing captured monitoring data, e.g. for logfile generation
• CPC Class Codes: H04W 4/70 Services for machine-to-machine communication [M2M] or machine type communication [MTC]

Abstract

A computer-implemented method for processing ECG data may include: receiving ECG data representing a plurality of heartbeats; analyzing the ECG data to determine whether each of the plurality of heartbeats is a normal heartbeat or an abnormal heartbeat; associating each of the abnormal heartbeats with an existing template or a new template; receiving input related to each new template, wherein the input includes either: a) a confirmation that the new template represents an abnormal heartbeat, or b) a reclassification of the new template as representing a normal heartbeat or a different abnormal heartbeat; and in response to the user input, updating a label of each of the heartbeats associated with each confirmed new template and each of the heartbeats associated with each reclassified new template.

Claims

1. A computer-implemented method for processing ECG data, comprising:

receiving, over an electronic network, ECG data, wherein the ECG data represents a plurality of heartbeats;

analyzing the ECG data, by at least one processor, to determine whether each of the plurality of heartbeats is a normal heartbeat or an abnormal heartbeat;

associating, by the at least one processor, each of the abnormal heartbeats with a label of;

at least one template of a plurality of existing templates, or

a new template;

after the associating of all of the abnormal heartbeats, receiving from a user, user input related to each new template, wherein the user input includes either;

a confirmation that the new template represents an abnormal heartbeat, or

a reclassification of the new template as representing a normal heartbeat or a different abnormal heartbeat;

after receiving the user input, updating, by the at least one processor, the label of each new template to correspond with the user input; and

determining, by the at least one processor, a number of abnormal heartbeats as a sum total of the heartbeats associated with (i) each template of the plurality of existing templates, (ii) each confirmed new template representing an abnormal heartbeat, and (iii) each new template reclassified as a different abnormal heartbeat, using the labels associated with the existing, confirmed new, and new reclassified templates.

2. The method of claim 1, wherein the method does not include repeating the analyzing step.

3. The method of claim 1, wherein the associating step includes comparing ECG data representing a heartbeat to at least one of the plurality of existing templates.

4. The method of claim 1, wherein the step of associating includes creating the new template for abnormal heartbeats having characteristics that differ by more than a predefined threshold from each of the existing templates.

5. The method of claim 1, wherein the step of associating an abnormal heartbeat with one of the plurality of existing templates includes associating the abnormal heartbeat with an existing template if the abnormal heartbeat has characteristics that differ by less than a predefined threshold from the existing template.

6. The method of claim 1, wherein the abnormal heartbeats include premature ventricular contractions.

7. The method of claim 1, wherein the electronic network includes a wireless connection over a cellular network.

8. The method of claim 1, wherein the receiving step includes receiving the ECG data from a monitor, and wherein the monitor is a portable device configured to be carried on a patient'"'"'s body.

9. A system for processing ECG data, comprising:

a data storage device that stores instructions for processing ECG data; and

a processor configured to execute the instructions to perform a method including;

receiving, over an electronic network, ECG data, wherein the ECG data represents a plurality of heartbeats;

analyzing the ECG data to determine whether each of the plurality of heartbeats is a normal heartbeat or an abnormal heartbeat;

associating each of the abnormal heartbeats with a label of;

at least one template of a plurality of existing templates, or

a new template;

after the associating of all of the abnormal heartbeats, receiving from a user, user input related to each new template, wherein the user input includes either;

a confirmation that the new template represents an abnormal heartbeat, or

a reclassification of the new template as representing a normal heartbeat or a different abnormal heartbeat;

after receiving the user input, updating the label of each new template to correspond with the user input; and

determining a number of abnormal heartbeats as a sum total of the heartbeats associated with a (i) each template of the plurality of existing templates, (ii) each confirmed new template representing an abnormal heartbeat, and (iii) each new template reclassified as a different abnormal heartbeat, using the labels associated with the existing, confirmed new, and new reclassified templates.

10. The system of claim 9, wherein the method performed by the processor does not include repeating the analyzing step.

11. The system of claim 9, wherein the step of associating includes comparing ECG data representing a heartbeat to at least one of the plurality of existing templates.

12. The system of claim 9, wherein the step of associating includes creating the new template for abnormal heartbeats having characteristics that differ by more than a predefined threshold from each of the existing templates.

13. The system of claim 9, wherein the step of associating an abnormal heartbeat with one of the plurality of existing templates includes associating the abnormal heartbeat with an existing template if the abnormal heartbeat has characteristics that differ by less than a predefined threshold from the existing template.

14. The system of claim 9, wherein the abnormal heartbeats include premature ventricular contractions.

15. A non-transitory computer-readable medium storing instructions that, when executed by a computer, cause the computer to perform a method for processing ECG data, the method including:

receiving, over an electronic network, ECG data, wherein the ECG data represents a plurality of heartbeats;

analyzing the ECG data, by at least one processor, to determine whether each of the plurality of heartbeats is a normal heartbeat or an abnormal heartbeat;

associating, by the at least one processor, each of the abnormal heartbeats with a label of;

at least one template of a plurality of existing templates, or

a new template;

after the associating of all of the abnormal heartbeats, receiving from a user, user input related to each new template, wherein the user input includes either;

a confirmation that the new template represents an abnormal heartbeat, or

a reclassification of the new template as representing a normal heartbeat or a different abnormal heartbeat;

after receiving the user input, updating, by the at least one processor, the label of each new template to correspond with the user input; and

determining, by the at least one processor, a number of abnormal heartbeats as a sum total of the heartbeats associated with (i) each template of the plurality of existing templates, (ii) each confirmed new template representing an abnormal heartbeat, and (iii) each new template reclassified as a different abnormal heartbeat, using the labels associated with the existing, confirmed new, and new reclassified templates.

16. The method of claim 15, wherein the method does not include repeating the analyzing step.

17. The method of claim 15, wherein the associating step includes comparing ECG data representing a heartbeat to at least one of the plurality of existing templates.

18. The method of claim 15, wherein the step of associating includes creating the new template for abnormal heartbeats having characteristics that differ by more than a predefined threshold from each of the existing templates.

19. The method of claim 15, wherein the step of associating an abnormal heartbeat with one of the plurality of existing templates includes associating the abnormal heartbeat with an existing template if the abnormal heartbeat has characteristics that differ by less than a predefined threshold from the existing template.

20. The method of claim 15, wherein the abnormal heartbeats include premature ventricular contractions.