System and method for monitoring and classifying atrial fibrillations

Patent metadata

Field	Value
Publication number	US-2016361024-A1
Application number	US-201514739399-A
Country	US
Kind code	A1
Filing date	Jun 15, 2015
Priority date	Jun 15, 2015
Publication date	Dec 15, 2016
Grant date	—

Abstract

A system and method of detecting and classifying atrial fibrillations (AFs) monitors an electro-cardiogram (ECG) signal of the patient. Based on the monitored ECG signals, AF episodes are detected. Monitored physiological parameters are utilized to determine an activity level of the patient at the time of the detected AF episode, wherein the activity level is associated with the detected AF episode. The etiology of the detected AF episodes is classified as adrenergic if the AF episodes occur while the patient is active, and classified as vagal if the AF episodes occur while the patient is at rest.

First claim

1 . A method of detecting and classifying atrial fibrillations (AFs), the method comprising:
monitoring an electro-cardiogram (ECG) signal of the patient; detecting atrial fibrillation (AF) episodes based on the monitored ECG signal; monitoring one or more physiological parameters to determine an activity level of the patient; associating a detected AF episode with an activity level of the patient at a time of the detected arrhythmia; classifying a cause of the detected AF episodes as adrenergic if detected AF episodes occur when the patient is active and classifying the cause of the detected AF episodes as vagal if detected AF episodes occur when the patient is at rest; and generating a report regarding the determined classification of the AF episodes.

2 . The method of claim 1 , wherein monitoring of the ECG signal and detection of AF episodes is provided for a prescribed monitoring period.

3 . The method of claim 2 , wherein in response to a detected AF episode during a period of patient activity, a count of active AF episodes detected within the prescribed monitoring period is incremented and wherein in response to a detected AF episode during a period of patient rest, a count of resting AF episodes detected within the prescribed monitoring period is incremented.

4 . The method of claim 4 , wherein classifying a cause of the detected AF episodes as adrenergic or vagal is based on the count of active AF episodes and the count of resting episodes detected with the prescribing monitoring period.

5 . The method of claim 1 , wherein in response to a detected AF episode during a period of patient activity, an ECG strip representing the detected AF episode is communicated to a remote center for verification, wherein only ECG strips representing verified AF episodes are retained.

6 . The method of claim 5 , wherein verified AF episodes are included in the generated report regarding the determined classification of the AF episodes.

7 . The method of claim 5 , wherein up to a maximum number of ECG strips representing AF episodes are communicated to the remote center for verification, wherein once the maximum number of ECG strips representing AF episodes have been communicated and verified, no additional ECG strips are communicated to the remote center.

8 . The method of claim 1 , further including capturing additional physiological parameters associated with the patient with respect to a detected AF episode for inclusion in the generated report.

9 . An adherent device comprising:
a plurality of electrodes and sensing circuitry for monitoring an electrocardiogram (ECG) signal of a patient to which the adherent device is affixed; an activity sensor for monitoring an activity level of the patient; and a processing module configured to receive the monitored ECG signal and the monitored activity level, wherein the processing module detects atrial fibrillation episodes based on the monitored ECG signal and associates with each detected AF episode an activity level monitored at the time of the AF episode, wherein the processing module maintains data related to detected AF episodes and activity level associated with the detected AF episodes and classifies an etiology of the detected AF episodes as adrenergic or vagal based on the maintained data.

10 . The adherent device of claim 9 , wherein data maintained by the processing module includes a count of AF episodes that occur during periods of patient rest and a count of AF episodes that occur during periods of patient activity.

11 . The adherent device of claim 9 , wherein data maintained by the processing module includes a total duration of AF episodes that occur during periods of patient rest and a total duration of AF episodes that occur during periods of patient activity.

12 . The adherent device of claim 9 , wherein in response to a detected AF episode, the processing module communicates an ECG strip including information related to the detected AF episode to a remote center for review and verification of the detected AF episode.

13 . The adherent device of claim 12 , wherein during a monitoring period, a maximum number of ECG strips are communicated to the remote center for review, wherein after the maximum number of ECG strips have been communicated and verified, subsequent AF episodes are utilized to update maintained data but are not communicated to the remote center for verification.

14 . The adherent device of claim 9 , wherein the processing module generates a report that includes at most a maximum number of ECG strips, a count of resting AF episodes that occurred during the monitoring period, and a count of active AF episodes that occurred during the monitoring period.

15 . The adherent device of claim 14 , wherein the processing module further includes in the generated report one or more of time of day, patient posture, and respiration rate as compared with resting AF episodes and active AF episodes.

Assignees

• Medtronic Monitoring Inc

Inventors

• Chakravarthy Niranjan
• Chavan Abhi

Classifications

• A61B5/7289

  Retrospective gating, i.e. associating measured signals or images with a physiological event after the actual measurement or image acquisition, e.g. by simultaneously recording an additional physiological signal during the measurement or image acquisition · CPC title

• A61B2562/04

  Arrangements of multiple sensors of the same type · CPC title

• A61B5/1118

  Determining activity level · CPC title

• A61B5/7278

  Artificial waveform generation or derivation, e.g. synthesizing signals from measured signals · CPC title

• A61B5/7264 Primary

  Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems · CPC title