Apparatus and method for discriminating between cardiac rhythms on the basis of their morphology using a neural network

Claim 1

A device for monitoring and classifying cardiac rhythms of a patient's heart, comprising: means for coupling to at least one of an atrium and a ventricle of the heart, for sensing respective ones of an atrial and a ventricular thereof as waveforms which are characteristic of respective cardiac rhythms; feature extraction means coupled to said coupling means and responsive to the sensed waveforms, for extracting from said waveforms features relating to the timing of events and the morphology of the waveforms; neural network means coupled to said feature extraction means for classifying said morphological features, said neural network means further including first means for discriminating between features relating to rhythms of normal origin and rhythms of pathological origin, and second means for discriminating between features relating to different kinds of tachycardia of pathological origin said first and second discriminating means generating output signals classifying cardiac rhythms into physiological and pathological categories; wherein said neural network means includes means for setting a time interval; wherein said feature extraction means includes a threshold tracking peak detector means to provide at least one fiducial point in each sensed waveform, said fiducial point being one of a maximum positive and minimum negative peak within said time of the threshold being exceeded by the waveform; wherein said feature extraction means integrates the waveform about its fiducial point for a predetermined period of time before and after said point.

Claim 2

A device for monitoring and classifying cardiac rhythms of a patient's heart, comprising: means for coupling to at least one of an atrium and a ventricle of the heart, for sensing respective ones of an atrial and a ventricular thereof as waveforms which are characteristic of respective cardiac rhythms; feature extraction means coupled to said coupling means and responsive to the sensed waveforms, for extracting from said waveforms features relating to the timing of events and the morphology of the waveforms; neural network means coupled to said feature extraction means for classifying said morphological features, said neural network means further including first means for discriminating between features relating to rhythms of normal origin and rhythms of pathological origin, and second means for discriminating between features relating to different kinds of tachycardia of pathological origin said first and second discriminating means generating output signals classifying cardiac rhythms into physiological and pathological categories; wherein said neural network means includes means for setting a time interval; wherein said feature extraction means includes a threshold tracking peak detector means to provide at least one fiducial point in each sensed waveform, said fiducial point being one of a maximum positive and minimum negative peak within said time of the threshold being exceeded by the waveform; wherein said feature extraction means integrates the waveform about its fiducial point for a predetermined period of time before and after said point.

Claim 4

A device for monitoring and classifying cardiac rhythms of a patient's heart, comprising: means for coupling to at least one of an atrium and a ventricle of the heart, for sensing respective ones of an atrial and a ventricular waveforms which are characteristic of respective cardiac rhythms; feature extraction means coupled to said coupling means and responsive to the sensed waveforms, for extracting from said waveforms features relating to the timing of events and the morphology of the waveforms; neural network means coupled to said feature extraction means for classifying said morphological features, said neural network means further including first means for discriminating between features relating to rhythms of normal origin and rhythms of pathological origin, and second means for discriminating between features relating to different kinds of tachycardia of pathological origin wherein said neural network means includes means for setting a time interval; said first and second discriminating means generating output signals classifying cardiac rhythms into physiological and pathological categories; wherein said feature extraction means includes a threshold tracking peak detector means to provide at least one fiducial point in each sensed waveform, said fiducial point being one of a maximum positive and minimum negative peak within a preselected time of the threshold being exceeded by the waveform; wherein said feature extraction means takes sums of differences of samples taken at predetermined intervals from the waveform symmetrically about its fiducial point.

Claim 5

A device for monitoring and classifying cardiac rhythms of a patient's heart, comprising: means for coupling to at least one of an atrium and a ventricle of the heart, for sensing respective ones of an atrial and a ventricular waveforms which are characteristic of respective cardiac rhythms; feature extraction means coupled to said coupling means and responsive to the sensed waveforms, for extracting from said waveforms features relating to the timing of events and the morphology of the waveforms; neural network means coupled to said feature extraction means for classifying said morphological features, said neural network means further including first means for discriminating between features relating to rhythms of normal origin and rhythms of pathological origin, and second means for discriminating between features relating to different kinds of tachycardia of pathological origin wherein said neural network means includes means for setting a time interval; said first and second discriminating means generating output signals classifying cardiac rhythms into physiological and pathological categories; wherein said feature extraction means includes a threshold tracking peak detector means to provide at least one fiducial point in each sensed waveform, said fiducial point being one of a maximum positive and minimum negative peak within a preselected time of the threshold being exceeded by the waveform; wherein said feature extraction means takes sums of differences of samples taken at predetermined intervals from the waveform symmetrically about its fiducial point.

Claim 6

A device for monitoring and classifying cardiac rhythms of a patient's heart, comprising: means for coupling to at least one of an atrium and a ventricle of the heart, for sensing respective ones of an atrial and a ventricular waveforms which are characteristic of respective cardiac rhythms; feature extraction means coupled to said coupling means and responsive to the sensed waveforms, for extracting from said waveforms features relating to the timing of events and the morphology of the waveforms; neural network means coupled to said feature extraction means for classifying said morphological features, said neural network means further including first means for discriminating between features relating to rhythms of normal origin and rhythms of pathological origin, and second means for discriminating between features relating to different kinds of tachycardia of pathological origin wherein said neural network means includes means for setting a time interval; said first and second discriminating means generating output signals classifying cardiac rhythms into physiological and pathological categories; wherein said feature extraction means includes a threshold tracking peak detector means to provide at least one fiducial point in each sensed waveform, said fiducial point being one of a maximum positive and minimum negative peak within a preselected time of the threshold being exceeded by the waveform; wherein said feature extraction means further includes a plurality of bandpass filters and integrators for filtering the waveform through said filters and integrators during the interval between successive fiducial points.

Claim 7

A device for monitoring and classifying cardiac rhythms of a patient's heart, comprising: means for coupling to at least one of an atrium and a ventricle of the heart, for sensing respective ones of an atrial and a ventricular waveforms which are characteristic of respective cardiac rhythms; feature extraction means coupled to said coupling means and responsive to the sensed waveforms, for extracting from said waveforms features relating to the timing of events and the morphology of the waveforms; neural network means coupled to said feature extraction means for classifying said morphological features, said neural network means further including first means for discriminating between features relating to rhythms of normal origin and rhythms of pathological origin, and second means for discriminating between features relating to different kinds of tachycardia of pathological origin wherein said neural network means includes means for setting a time interval; said first and second discriminating means generating output signals classifying cardiac rhythms into physiological and pathological categories; wherein said feature extraction means includes a threshold tracking peak detector means to provide at least one fiducial point in each sensed waveform, said fiducial point being one of a maximum positive and minimum negative peak within a preselected time of the threshold being exceeded by the waveform; wherein said feature extraction means further includes a plurality of bandpass filters and integrators for filtering the waveform through said filters and integrators during the interval between successive fiducial points.

Claim 8

A device for monitoring and classifying cardiac rhythms of a patient's heart, comprising: means for coupling to at least one of an atrium and a ventricle of the heart, for sensing respective one of an atrial and a ventricular thereof as waveforms which are characteristic of respective cardiac rhythms; feature extraction means coupled to said coupling means and responsive to the sensed waveforms, for extracting from said waveforms features relating to the timing of events and the morphology of the waveforms; neural network means coupled to said feature extraction means for classifying said morphological features, said neural network means further including first means for discriminating between features relating to rhythms of normal origin and rhythms of pathological origin, and second means for discriminating between features relating to different kinds of tachycardia of pathological origin; wherein said neural network means includes means for setting a time interval; said first and second discriminating means generating output signals classifying cardiac rhythms into physiological and pathological categories; wherein said feature extraction means includes a threshold tracking peak detector means to provide at least one fiducial point in each sensed waveform, said fiducial point being one of a maximum positive and minimum negative peak within a preselected time of the threshold being exceeded by the waveform; wherein said feature extraction means further includes means for determining the crossings of a waveform through zero amplitude for determining the crossings of the waveforms through zero amplitude.

Claim 9

A device for monitoring and classifying cardiac rhythms of a patient's heart, comprising: means for coupling to at least one of an atrium and a ventricle of the heart, for sensing respective one of an atrial and a ventricular thereof as waveforms which are characteristic of respective cardiac rhythms; feature extraction means coupled to said coupling means and responsive to the sensed waveforms, for extracting from said waveforms features relating to the timing of events and the morphology of the waveforms; neural network means coupled to said feature extraction means for classifying said morphological features, said neural network means further including first means for discriminating between features relating to rhythms of normal origin and rhythms of pathological origin, and second means for discriminating between features relating to different kinds of tachycardia of pathological origin; wherein said neural network means includes means for setting a time interval; said first and second discriminating means generating output signals classifying cardiac rhythms into physiological and pathological categories; wherein said feature extraction means includes a threshold tracking peak detector means to provide at least one fiducial point in each sensed waveform, said fiducial point being one of a maximum positive and minimum negative peak within a preselected time of the threshold being exceeded by the waveform; wherein said feature extraction means further includes means for determining the crossings of a waveform through zero amplitude for determining the crossings of the waveforms through zero amplitude.

Claim 10

A device for monitoring and classifying cardiac rhythms of a patient's heart, comprising: means for coupling to at least one of an atrium and a ventricle of the heart, for sensing respective ones of an atrial and a ventricular thereof as waveforms which are characteristic of respective cardiac rhythms; feature extraction means coupled to said coupling means and responsive to the sensed waveforms, for extracting from said waveforms features relating to the timing of events and the morphology of the waveforms; neural network means coupled to said feature extraction means for classifying said morphological features, said neural network means further including first means for discriminating between features relating to rhythms of normal origin and rhythms of pathological origin, and second means for discriminating between features relating to different kinds of tachycardia of pathological origin; wherein said neural network means includes means for setting a time interval; said first and second discriminating means generating output signals classifying cardiac rhythms into physiological and pathological categories; wherein said feature extraction means includes a threshold tracking peak detector means to provide at least one fiducial point in each sensed waveform, said fiducial point being one of a maximum positive and minimum negative peak within a preselected time of the threshold being exceeded by the waveform; wherein said feature extraction means determines an interval between successive atrial and ventricular complexes of the waveform; and wherein said classifying means classifies as of pathological origin those of such tachycardias in which atrioventricular intervals change rapidly in sequence.

Claim 11

A device for monitoring and classifying cardiac rhythms of a patient's heart, comprising: means for coupling to at least one of an atrium and a ventricle of the heart, for sensing respective ones of an atrial and a ventricular thereof as waveforms which are characteristic of respective cardiac rhythms; feature extraction means coupled to said coupling means and responsive to the sensed waveforms, for extracting from said waveforms features relating to the timing of events and the morphology of the waveforms; neural network means coupled to said feature extraction means for classifying said morphological features, said neural network means further including first means for discriminating between features relating to rhythms of normal origin and rhythms of pathological origin, and second means for discriminating between features relating to different kinds of tachycardia of pathological origin; wherein said neural network means includes means for setting a time interval; said first and second discriminating means generating output signals classifying cardiac rhythms into physiological and pathological categories; wherein said feature extraction means includes a threshold tracking peak detector means to provide at least one fiducial point in each sensed waveform, said fiducial point being one of a maximum positive and minimum negative peak within a preselected time of the threshold being exceeded by the waveform; wherein said feature extraction means determines an interval between successive atrial and ventricular complexes of the waveform; and wherein said classifying means classifies as of pathological origin those of such tachycardias in which atrioventricular intervals change rapidly in sequence.