Internet-based system for evaluating T waves within ECG waveforms to determine the presence of cardiac abnormalities

• US 9,554,719 B2
• Filed: 10/08/2013
• Issued: 01/31/2017
• Est. Priority Date: 10/08/2012
• Status: Active Grant

• Current Assignee: Baxter Healthcare SA (Baxter International Inc.), Baxter International Inc.
• Original Assignee: OtoSense, Inc. (Analog Devices, Inc.)
• Inventors: Dillon, Marshal Singh, Banet, Matthew, Feld, Gregory Kent, Meza-Guinea, Adolfo, Pede, Susan Meeks, Terry, Andrew
• Primary Examiner(s): Koharski, Christopher D
• Assistant Examiner(s): Patel, Natasha
• Application Number:
  US14/048,723
• Publication Number:
  US 20150005650A1
• Time in Patent Office: 1,211 Days
• US Class Current: 1/1
• 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 5/349 Detecting specific parameters of the electrocardiograph cycle
• CPC Class Codes: A61B 5/361 Detecting fibrillation
• CPC Class Codes: A61B 5/363 Detecting tachycardia or bradycardia
• CPC Class Codes: A61B 5/364 Detecting abnormal ECG interval, e.g. extrasystoles, ectopic heartbeats
• CPC Class Codes: G16H 40/67 for remote operation
• CPC Class Codes: Y02A 90/10 Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation

Abstract

The present invention provides an improved, Internet-based system that seamlessly collects cardiovascular data from a patient before, during, and after a procedure for EP or an ID. During an EP procedure, the system collects information describing the patient'"'"'s response to PES and the ablation process, ECG waveforms and their various features, HR and other vital signs, HR variability, cardiac arrhythmias, patient demographics, and patient outcomes. Once these data are collected, the system stores them on an Internet-accessible computer system that can deploy a collection of user-selected and custom-developed algorithms. Before and after the procedure, the system also integrates with body-worn and/or programmers that interrogate implanted devices to collect similar data while the patient is either ambulatory, or in a clinic associated with the hospital. A data-collection/storage module, featuring database interface, stores physiological and procedural information measured from the patient.

Claims

1. A system for determining the presence of cardiac abnormalities in a patient by evaluating T waves from the patient'"'"'s ECG waveform, comprising:

(i) a body-worn ECG monitoring system configured to obtain ECG waveforms from the patient comprising;

at least 2 ECG electrodes,

a processing unit comprising a first microprocessor, an analog-to-digital converter, and a wireless transmitter, the processing unit operably connected to the ECG electrodes and configured to receive and process electrical signals therefrom to generate one or more digital ECG waveforms, the processing unit further configured to identify one or more features corresponding to one or more heartbeats in the one or more digital ECG waveforms and to wirelessly transmit the one or more features and the digital ECG waveforms;

(ii) a computer system comprising;

a database stored on a non-transitory computer-readable storage medium, the database comprising a set of data fields collected from a plurality of individuals, with each data field in the set corresponding to an individual within the plurality of individuals and including a T wave extracted from an ECG waveform obtained from the individual and a parameter indicating the presence of a cardiac abnormality in the individual, and

a second microprocessor operably connected to the processing unit to receive the one or more features and the one or more digital ECG waveforms wirelessly transmitted by the processing unit, and operably connected to the non-transitory computer-readable storage medium to access the database to store the one or more features and the one or more digital ECG waveforms in a data field corresponding to the patient;

wherein the second microprocessor performs an ECG-analysis algorithm that processes the one or more ECG waveforms to extract therefrom a set of parameters corresponding to the T wave in the one or more heartbeats,

wherein the second microprocessor performs an averaging algorithm by processing a plurality of data fields, each data field corresponding to an individual within the plurality of individuals to determine an average correlation factor mapping the parameters corresponding to the T wave to the parameter indicating the presence of a cardiac abnormality, and

wherein the second microprocessor performs a correlation algorithm configured to evaluate the presence of a cardiac abnormality in the patient by comparing the set of parameters corresponding to the T wave in the one or more heartbeats to the average correlation factor to estimate a new parameter indicating the presence of a cardiac abnormality in the patient, and to store the new parameter in the data field corresponding to the patient.

2. The system of claim 1, wherein the ECG-analysis algorithm is further configured to process the ECG waveform to determine the temporal location of the T wave.

3. The system of claim 1, wherein the ECG-analysis algorithm is further configured to process the ECG waveform to determine the amplitude of the T wave.

4. The system of claim 3, wherein the average correlation factor correlates an amplitude of the T wave to the presence of a cardiac abnormality in the patient.

5. The system of claim 4, wherein the correlation algorithm is further configured to determine the presence of a cardiac abnormality in the patient when the amplitude of the T wave is less than a baseline of the ECG waveform.

6. The system of claim 5, wherein the correlation algorithm is further configured to determine the presence of at least one of myocardial ischemia, myocardial infarction, pericarditis, ventricular enlargement, bundle branch block, subarachnoid hemorrhage when the amplitude of the T wave is less than a baseline of the ECG waveform.

7. The system of claim 5, wherein the correlation algorithm is further configured to determine the presence of a cardiac abnormality in the patient when the amplitude of the T wave is inverted.

8. The system of claim 5, wherein the correlation algorithm is further configured to determine the presence of at least one of myocardial ischemia, myocardial infarction, pericarditis, ventricular enlargement, bundle branch block, and subarachnoid hemorrhage when the amplitude of the T wave is inverted.

9. The system of claim 1, wherein the database, ECG-analysis algorithm, averaging algorithm, and correlation algorithm are comprised by an Internet-accessible system.

10. The system of claim 9, wherein the Internet-accessible system further comprises a graphical user interface (GUI).

11. The system of claim 10, wherein the GUI comprises a webpage that displays the new parameter indicating the presence of at least one of myocardial ischemia, myocardial infarction, pericarditis, ventricular enlargement, bundle branch block, and subarachnoid hemorrhage.

12. The system of claim 1, wherein the ECG-measuring system comprises an ECG circuit configured to be worn on the patient'"'"'s body, and a transmitting circuit configured to transmit a numerical representation of the ECG waveform to the database.

13. The system of claim 12, wherein the transmitting circuit is configured to transmit the numerical representation of the ECG waveform to an Ethernet port, which then transmits the numerical representation of the ECG waveform to an IP address associated with the database.

14. The system of claim 12, wherein the transmitting circuit is configured to transmit the numerical representation of the ECG waveform to a mobile device, which then transmits the numerical representation of the ECG waveform to an IP address associated with the database.

15. A system for evaluating a presence of at least one of myocardial ischemia, myocardial infarction, pericarditis, ventricular enlargement, bundle branch block, and subarachnoid hemorrhage in a patient, comprising:

(i) a body-worn ECG monitoring system comprising;

at least 3 ECG electrodes,

a processing unit comprising a first microprocessor, an analog-to-digital converter, and a wireless transmitter, the processing unit operably connected to the ECG electrodes and configured to receive and process electrical signals therefrom to generate one or more digital ECG waveforms, the processing unit further configured to identify one or more features corresponding to each heartbeat in the one or more digital ECG waveforms and to wirelessly transmit the one or more features and the digital ECG waveforms;

(ii) a computer system comprising;

a database stored on a non-transitory computer-readable storage medium, the database comprising a set of data fields collected from a plurality of individuals, with each data field in the set corresponding to an individual within the plurality of individuals and including a T wave extracted from an ECG waveform obtained from the individual and a parameter indicating the presence of at least one of myocardial ischemia, myocardial infarction, pericarditis, ventricular enlargement, bundle branch block, and subarachnoid hemorrhage in the individual, and

a second microprocessor operably connected to the processing unit to receive the one or more features and the one or more digital ECG waveforms wirelessly transmitted by the processing unit, and operably connected to the non-transitory computer-readable storage medium to access the database to store the one or more features and the one or more digital ECG waveforms in a data field corresponding to the patient;

wherein the second microprocessor performs an ECG-analysis algorithm that processes the one or more ECG waveforms to extract therefrom a set of parameters corresponding to the T wave in the one or more heartbeats,

wherein the second microprocessor performs an averaging algorithm by processing a plurality of data fields, each data field corresponding to an individual within the plurality of individuals to determine an average correlation factor mapping the set parameters corresponding to the T wave to the parameter indicating at least one of myocardial ischemia, myocardial infarction, pericarditis, ventricular enlargement, bundle branch block, and subarachnoid hemorrhage, and

wherein the second microprocessor performs a correlation algorithm configured to evaluate the presence of at least one of myocardial ischemia, myocardial infarction, pericarditis, ventricular enlargement, bundle branch block, and subarachnoid hemorrhage in the patient by comparing the set of parameters corresponding to the T wave in the one or more heartbeats to the average correlation factor to estimate a new parameter indicating the presence of at least one of myocardial ischemia, myocardial infarction, pericarditis, ventricular enlargement, bundle branch block, and subarachnoid hemorrhage, and to store the new parameter in the data field corresponding to the patient.