Prediction and prevention of postoperative atrial fibrillation in cardiac surgery patients

Patent metadata

Field	Value
Publication number	US-9636033-B2
Application number	US-201213419463-A
Country	US
Kind code	B2
Filing date	Mar 14, 2012
Priority date	Sep 19, 2006
Publication date	May 2, 2017
Grant date	May 2, 2017

Abstract

Systems and methods are provided for predicting the onset of postoperative atrial fibrillation (AF) from electrocardiogram (ECG) data representing a patient. A signal processing component determines parameters representing the activity of the heart of the patient from the ECG data. A feature extraction component calculates a plurality of features useful in predicting postoperative AF from the determined parameters. A classification component determines an AF index for the patient from the calculated plurality of features. The AF index represents the likelihood that the patient will experience AF.

First claim

Having described the invention, the following is claimed:

1. A non-transitory computer readable medium containing computer executable instructions that can be executed by a processor to predict the onset of atrial fibrillation (AF) from electrocardiogram (ECG) data representing a patient, the executable instructions comprising:
a signal processing component that determines parameters representing the activity of the heart of the patient from the ECG data, the signal processing component comprising a premature atrial contraction (PAC) detection system that identifies premature atrial contractions represented by the ECG data;
a feature extraction component that calculates a plurality of features from the determined parameters, at least one feature being calculated from the detected premature atrial contractions; and
a classification component that determines an AF index for the patient, representing the likelihood that the patient will experience AF, from the calculated plurality of features;
wherein the AF index is output to a cardiac monitoring apparatus.

2. The non-transitory computer readable medium of claim 1 , the PAC detection system comprising a plurality of irregular beat detectors that identify irregular heart beats of the patient within respective ECG channels.

3. The non-transitory computer readable medium of claim 2 , the PAC detection system comprising:
a plurality of ventricular event evaluators, each ventricular event detector evaluating the output of one of the plurality of irregular beat detectors to distinguish between premature atrial beats and premature ventricular beats; and
an inter-channel comparator that receives the outputs of the plurality of ventricular event evaluators and confirms PAC occurrences by ensuring that a given premature atrial beat is detected in a threshold number of channels.

4. The non-transitory computer readable medium of claim 1 , the classification component comprising a fuzzy logic classifier.

5. The non-transitory computer readable medium of claim 1 , the feature extractor calculating at least one feature representing heart rate variability in the frequency domain.

6. The non-transitory computer readable medium of claim 1 , the feature extractor calculating at least one feature representing P-wave morphology parameters.

7. The non-transitory computer readable medium of claim 1 , one of the plurality of features calculated by the feature extraction component comprising a nonlinear measure of heart rate variability.

Assignees

• Bashour C Allen
• Nair Bala Gopakumaran
• Visinescu Mirela
• Xu Meng
• Li Liang
• Bakri Mohamed H
• Cleveland Clinic Found

Inventors

• Bashour C Allen
• Nair Bala Gopakumaran
• Visinescu Mirela
• Xu Meng
• Li Liang
• Bakri Mohamed H

Classifications

• A61B5/7275

  Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor · CPC title

• A61B5/046

  Human Necessities · mapped topic

• G06F19/3431

  Physics · mapped topic

• A61B5/726

  using Wavelet transforms · CPC title

• A61B5/02405 Primary

  Determining heart rate variability · CPC title