US-12616368-B2 - Beat reclassification

Abstract

A method includes receiving, by a first computing system, electrocardiogram (ECG) data and metadata associated with the ECG data. The metadata includes an initial cardiac event classification and an initial beat classification for beats occurring during a first event associated with the initial cardiac event classification. The method further includes displaying the ECG data in a user interface, receiving a command to change the initial cardiac event classification to a subsequent cardiac event classification, and automatically modifying the initial beat classifications to subsequent beat classifications based on the subsequent cardiac event classification.

Inventors

• David Robert Engebretsen
• Jake Matras
• Timothy Patrick McClanahan
• Benjamin Adam TEPLITZKY
• Michael Thomas Edward McRoberts

Assignees

• PREVENTICE SOLUTIONS, INC.

Dates

Publication Date

20260505

Application Date

20230426

Claims (18)

1. 1 . A system comprising: a remote computing system comprising: a user interface (UI), a first processor, and a first computer-readable medium having a first set of computer-executable instructions embodied thereon, the first set of instructions configured to be executed to cause the remote computing system to: after receiving electrocardiogram (ECG) data, the first set of computer-executable instructions, and metadata including an initial cardiac event classification and an initial beat classification for each beat occurring during a first event associated with the initial cardiac event classification: display the ECG data in the UI; receive a command, via user input to the UI, to change the initial cardiac event classification to a subsequent cardiac event classification; modify the initial cardiac event classification of the first event to the subsequent cardiac event classification; and automatically modify the initial beat classifications to subsequent beat classifications based on the subsequent cardiac event classification selected via the UI.
2. 2 . The system of claim 1 , wherein the initial cardiac event classification is an atrial fibrillation event, a normal sinus event, or a supraventricular event, wherein the subsequent cardiac event classification is a ventricular tachycardia event, wherein the subsequent beat classifications are ventricular beats.
3. 3 . The system of claim 1 , wherein the initial cardiac event classification is a ventricular tachycardia event or a supraventricular event, wherein the subsequent cardiac event classification is a normal sinus event, wherein the subsequent beat classifications are normal beats.
4. 4 . The system of claim 1 , wherein the initial cardiac event classification is a ventricular tachycardia event or a supraventricular event, wherein the subsequent cardiac event classification is an atrial fibrillation event, wherein the subsequent beat classifications are normal beats.
5. 5 . The system of claim 1 , wherein the initial beat classifications include a first beat type and a second beat type, wherein the automatically modifying the initial beat classifications to the subsequent beat classifications comprises modifying only the first beat type.
6. 6 . The system of claim 1 , wherein the first set of instructions are configured to be executed by the first processor to cause the first processor to: display, in the UI, the initial beat classifications and the initial cardiac event classification; and after the automatically modifying step, display the subsequent beat classifications and the subsequent cardiac event classification.
7. 7 . The system of claim 1 , wherein the first set of instructions are configured to be executed via a web browser at the remote computing system.
8. 8 . The system of claim 1 , further comprising: a server comprising: a database, a second processor, and a second computer-readable medium having a second set of computer-executable instructions embodied thereon, the second set of instructions configured to be executed by the second processor to cause the second processor to: determine, using a machine learning model operated by the server and based on ECG data, the initial cardiac event classification and the initial beat classifications; store the initial cardiac event classification and initial beat classifications in the database; transmit, to the remote computing system, strips of the initial ECG data, the initial cardiac event classification, the initial beat classifications, and the first set of instructions; receive, from the remote computing system, the subsequent cardiac event classification and the subsequent beat classifications; and replace, in the database, the initial cardiac event classification with the subsequent cardiac event classification and the initial beat classifications with the subsequent beat classifications.
9. 9 . The system of claim 8 , wherein the first set of instructions are executed by a web browser at the remote computing system.
10. 10 . The system of claim 1 , wherein the automatically modify is carried out without using processing resources of a server.
11. 11 . A method comprising: receiving, by a first computing system, electrocardiogram (ECG) data and metadata associated with the ECG data, the metadata comprising an initial cardiac event classification and an initial beat classification for each separate beat occurring during a first event associated with the initial cardiac event classification; displaying the ECG data in a user interface (UI); receiving, via the UI, a command to change the initial cardiac event classification to a subsequent cardiac event classification; modifying the initial cardiac event classification of the first event to the subsequent cardiac event classification; and automatically modifying the initial beat classifications to subsequent beat classifications based on the subsequent cardiac event classification selected via the UI.
12. 12 . The method of claim 11 , wherein the initial cardiac event classification is an atrial fibrillation event, a normal sinus event, or a supraventricular event, wherein the subsequent cardiac event classification is a ventricular tachycardia event, wherein the subsequent beat classifications are ventricular beats.
13. 13 . The method of claim 11 , wherein the initial cardiac event classification is a ventricular tachycardia event or a supraventricular event, wherein the subsequent cardiac event classification is a normal sinus event, wherein the subsequent beat classifications are normal beats.
14. 14 . The method of claim 11 , wherein the initial cardiac event classification is a ventricular tachycardia event or a supraventricular event, wherein the subsequent cardiac event classification is an atrial fibrillation event, wherein the subsequent beat classifications are normal beats.
15. 15 . The method of claim 11 , wherein the initial beat classifications include a first beat type and a second beat type, wherein the automatically modifying the initial beat classifications to the subsequent beat classifications comprises modifying only the first beat type.
16. 16 . The method of claim 11 , wherein the subsequent beat classifications are determined by executing computer code by a web browser operating on the first computing system.
17. 17 . The method of claim 11 , further comprising: receiving, by the first computing system, executable computer code from a server, wherein the automatically modifying is carried out using the executable computer code using one or more microprocessors of the first computing system.
18. 18 . The method of claim 17 , wherein the automatically modifying is carried out without using processing resources of the server.

Description

CROSS REFERENCE TO RELATED APPLICATION This application claims priority to Provisional Application No. 63/335,621, filed Apr. 27, 2022, all of which are herein incorporated by reference in their entirety. TECHNICAL FIELD The present disclosure relates to devices, methods, and systems for analyzing cardiac activity and cardiac events. BACKGROUND Monitoring devices for collecting biometric data are becoming increasingly common in diagnosing and treating medical conditions in patients. For example, mobile devices can be used to monitor cardiac data in a patient. This cardiac monitoring can empower physicians with valuable information regarding the occurrence and regularity of a variety of heart conditions and irregularities in patients. Cardiac monitoring can be used, for example, to identify abnormal cardiac rhythms, so that critical alerts can be provided to patients, physicians, or other care providers and patients can be treated. SUMMARY In Example 1, a method includes receiving, by a first computing system, electrocardiogram (ECG) data and metadata associated with the ECG data. The metadata includes an initial cardiac event classification and an initial beat classification for beats occurring during a first event associated with the initial cardiac event classification. The method further includes displaying the ECG data in a user interface, receiving a command to change the initial cardiac event classification to a subsequent cardiac event classification, and automatically modifying the initial beat classifications to subsequent beat classifications based on the subsequent cardiac event classification. In Example 2, the method of Example 1, wherein the initial cardiac event classification is an atrial fibrillation event, a normal sinus event, or a ventricular tachycardia event, wherein the subsequent cardiac event classification is a supraventricular event, wherein the subsequent beat classifications are supraventricular beats. In Example 3, the method of Example 1, wherein the initial cardiac event classification is an atrial fibrillation event, a normal sinus event, or a supraventricular event, wherein the subsequent cardiac event classification is a ventricular tachycardia event, wherein the subsequent beat classifications are ventricular beats. In Example 4, the method of Example 1, wherein the initial cardiac event classification is a ventricular tachycardia event or a supraventricular event, wherein the subsequent cardiac event classification is a normal sinus event, wherein the subsequent beat classifications are normal beats. In Example 5, the method of Example 1, wherein the initial cardiac event classification is a ventricular tachycardia event or a supraventricular event, wherein the subsequent cardiac event classification is an atrial fibrillation event, wherein the subsequent beat classifications are normal beats. In Example 6, the method of any of the preceding Examples, wherein the initial beat classifications include a first beat type and a second beat type, wherein the automatically modifying the initial beat classifications to the subsequent beat classifications includes modifying only the first beat type. In Example 7, the method of any of the preceding Examples, further including displaying, in the UI, the initial beat classifications and the initial cardiac event classification and, after the automatically modifying step, displaying the subsequent beat classifications and the subsequent cardiac event classification. In Example 8, the method of any of the preceding Examples, wherein the initial beat classifications and the initial cardiac event classification are determined by a deep learning neural network operated by a server, wherein the subsequent beat classifications are determined by the first computing system. In Example 9, the method of Example 8, wherein the subsequent beat classifications are determined by executing computer code by a web browser operating on the first computing system. In Example 10, the method of Example 8, further including receiving, by the first computing system, the computer code in a data package that also includes the ECG data and the metadata. In Example 11, the method of any of the preceding Examples, wherein the command is generated in response to receiving input, via the UI, from a user. In Example 12, the method of any of the preceding Examples, further including receiving, by the first computing system, a second set of ECG data and a second set of metadata associated with the second set of ECG data. The second set of metadata includes a first cardiac event classification and a first beat classification for each beat occurring during a second event associated with the first cardiac event classification. The method further includes receiving a first command to change the first cardiac event classification to a second cardiac event classification and maintaining the first beat classifications to second beat classifications based on the second card