Atrial fibrillation detection method and apparatus
First Claim
1. An arrhythmia detection apparatus comprising:
- a beat classification module having an input to receive ECG information;
an interval calculator coupled to the beat classification module and operable to calculate an interval between recurring events;
a probability engine coupled to the interval calculator and operable to output a state variable;
a contextual analysis module coupled to the interval calculator and operable to match predefined maps to a current beat map and to generate a contextual output;
a P wave detection module coupled to the beat classification module and operable to produce a detection output; and
a state evaluation module coupled to the probability engine, the contextual analysis module, and the P wave detection module and operable to determine an arrhythmia condition based on the state variable, the contextual output, and the detection output.
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Abstract
A method and apparatus to detect irregular heart activity based upon a ventricular activity analysis, P wave activity, similarities in R wave to R wave intervals, and a state evaluation. The invention includes a beat classification module that receives ECG information as an input. The beat classification module determines whether the heart beat being analyzed falls within classifications that are suitable for use in analyzing whether an irregular condition exists. If the beat falls within a class suitable for analysis, the ECG information is fed to an interval calculator. The interval calculator determines the interval between successive R waves. The information from the interval calculator is provided to a probability engine and to a contextual analysis module. The probability engine is designed to detect atrial fibrillation based upon beat classification and RR interval values from the interval calculator. The probability engine outputs a state variable that indicates a probability of whether an irregular condition is present. The contextual analysis module matches predefined maps to a running map of the current ECG information. The contextual analysis module also determines the similarity between consecutive RR intervals and checks for sequences of matching classes. ECG information is also supplied to a P wave detection module to detect the presence of P waves. Information from the probability analysis engine, the contextual analysis module, and the P wave detection module is then provided to a state evaluation module. The state evaluation module uses the outputs of the three modules to determine whether an irregular condition exists.
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Citations
34 Claims
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1. An arrhythmia detection apparatus comprising:
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a beat classification module having an input to receive ECG information;
an interval calculator coupled to the beat classification module and operable to calculate an interval between recurring events;
a probability engine coupled to the interval calculator and operable to output a state variable;
a contextual analysis module coupled to the interval calculator and operable to match predefined maps to a current beat map and to generate a contextual output;
a P wave detection module coupled to the beat classification module and operable to produce a detection output; and
a state evaluation module coupled to the probability engine, the contextual analysis module, and the P wave detection module and operable to determine an arrhythmia condition based on the state variable, the contextual output, and the detection output. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A method of detecting an arrhythmia from ECG information, the method comprising:
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classifying the ECG information;
determining intervals between recurring events in the ECG information;
determining a probability that an irregular condition exists based on classifying the ECG information and determining an interval between recurring events;
generating a state variable based upon the determined probability;
generating a contextual output based on similarities in intervals between recurring events;
determining the presence of a P wave in the ECG information;
generating a detection output based on determining the presence of a P wave; and
determining the existence of the irregular condition based on the state variable, the contextual output, and the detection output. - View Dependent Claims (12, 13, 14, 15, 16, 17)
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18. A physiological condition detection apparatus comprising:
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a classification module having an input to receive physiological information;
an interval calculator coupled to the classification module and operable to calculate intervals between recurring events;
a probability engine coupled to the interval calculator and operable to output a state variable;
a contextual analysis module coupled to the interval calculator and operable to generate a contextual output based on the classification of the physiological information and the intervals between recurring events;
a wave detection module coupled to the classification module and operable to produce a detection output; and
a state evaluation module coupled to the probability engine, the contextual analysis module, and the wave detection module and operable to determine a physiological condition based on the state variable, the contextual output, and the detection output. - View Dependent Claims (19, 20, 21, 22, 23, 24, 25, 26, 27)
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28. A method of analyzing physiological information, the method comprising:
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classifying the physiological information;
determining intervals between recurring events in the physiological information;
determining a probability that an irregular condition exists based on classifying the physiological information and determining an interval between recurring events;
generating a state variable based upon the determined probability;
generating a contextual output based on similarities in intervals between recurring events;
determining the presence of a predetermined wave in the physiological information;
generating a detection output based on determining the presence of a predetermined wave; and
determining the existence of the irregular condition based on the state variable, the contextual output, and the detection output. - View Dependent Claims (29, 30, 31, 32, 33, 34)
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Specification