Techniques for determining whether a ventricular depolarization is a premature ventricular contraction (PVC) depolarization may include processing circuitry of a medical system identifying an interval from a maximum slope point to a minimum slope point for each of a plurality of ventricular depolarizations and, for each of the plurality of ventricular depolarizations as a current ventricular depolarization, determining that the intervals from the maximum slope point to the minimum slope point for the current ventricular depolarization, a preceding adjacent ventricular depolarization of the plurality of ventricular depolarizations, and a subsequent adjacent ventricular depolarization of the plurality of ventricular depolarizations satisfy one or more slope criteria. The processing circuitry determines that the current ventricular depolarization is a PVC depolarization based on the intervals from the maximum slope point to the minimum slope point satisfying the one or more slope criteria.

A system is provided for displaying heart graphic information relating to sources and source locations of a heart disorder to assist in evaluation of the heart disorder. A heart graphic display system provides an intra-cardiogram similarity (ICS) graphic and a source location (SL) graphic. The ICS graphic includes a grid with the x-axis and y-axis representing patient cycles of a patient cardiogram with the intersections of the patient cycle identifiers indicating similarity between the patient cycles. The SL graphic provides a representation of a heart with source locations indicated. The source locations are identified based on similarity of a patient cycle to library cycles of a library cardiogram of a library of cardiograms.

Electrocardiograms can be analyzed in the time-frequency domain, following conversion into time-frequency maps, to determine characteristics or features of various waveforms, such as waveform morphology and/or the amplitude(s) and location(s) (in time and/or frequency) of one or more extrema of the waveform. Based on comparison of the extrema against thresholds and/or against each other, disease conditions may be determined.

A system for processing cardiac activation information associated with a complex rhythm disorder identifies a location of the heart rhythm disorder by determining activations within cardiac signals obtained at neighboring locations of the heart and arranging the activations to identify an activation trail. The activation trail may define a rotational pattern or radially emanating pattern corresponding to an approximate core of the heart rhythm disorder.

A system is provided for generating a classifier for classifying electromagnetic data (e.g., ECG) derived from an electromagnetic source (e.g., heart). The system accesses a computational model of the electromagnetic source. The computational model models the electromagnetic output of the electromagnetic source over time based on a source configuration (e.g., rotor location) of the electromagnetic source. The system generates, for each different source configuration (e.g., different rotor locations), a modeled electromagnetic output (e.g., ECG) of the electromagnetic source for that source configuration. For each modeled electromagnetic output, the system derives the electromagnetic data for the modeled electromagnetic output and generates a label (e.g., rotor location) for the derived electromagnetic data from the source configuration for the modeled electromagnetic data. The system trains a classifier with the derived electromagnetic data and the labels as training data. The classifier can then be used to classify the electromagnetic output collected from patients.

Methods and systems are provided for detecting arrhythmias in cardiac activity. The methods and systems declare a current beat, from the CA signals, to be a candidate beat or an ineligible beat based on whether the current beat satisfies the rate based selection criteria. The determining and declaring operations are repeated for multiple beats to form an ensemble of candidate beats. The method and system calculate a P-wave segment ensemble from the ensemble of candidate beats, perform a morphology-based comparison between the P-wave segment ensemble and at least one of a monophasic or biphasic template, declare a valid P-wave to be present within the CA signals based on the morphology-based comparison, and utilize the valid P-wave in an arrhythmia detection process to determine at least one of an arrhythmia entry, arrhythmia presence or arrhythmia exit.

Methods, systems, and apparatus for detecting and/or validating a detection of a state change by matching the shape of one or more of an cardiac data series, a heart rate variability data series, or at least a portion of a heart beat complex, derived from cardiac data, to an appropriate template.

It is provided a method for analysing heart data of a user. The method is performed in an analysis device and comprises the steps of: obtaining, from the portable sensor device, first electrocardiogram data, based on electrical signals measured by electrodes placed on the torso of the user; obtaining, from the portable sensor device, second electrocardiogram data, based on electrical signals measured by electrodes placed on two separate arms of the user; evaluating the first electrocardiogram data to determine whether there are any first abnormalities; evaluating the second electrocardiogram data to determine whether there are any second abnormalities; and determining that the heart is considered to need further examination only when there are both first abnormalities and second abnormalities.

Systems and methods for classifying a cardiac arrhythmia are discussed. An exemplary system includes a correlator circuit to generate autocorrelation sequences using information of cardiac activity of a subject, including signal segments taken from a cardiac signal at respective elapsed time with respect to reference time. The correlator circuit can generate a correlation image using the autocorrelation sequences. The correlation image may be constructed by stacking the autocorrelation sequences according to the elapsed time of signal segments. An arrhythmia classifier circuit can classify the cardiac activity of the subject as one of arrhythmia types using the correlation image.

A medical device, such as an extra-cardiovascular implantable cardioverter defibrillator (ICD), senses R-waves from a first cardiac electrical signal by a first sensing channel and stores a time segment of a second cardiac electrical signal acquired by a second sensing channel in response to each sensed R-wave. The ICD determines morphology match scores from the stored time segments of the second cardiac electrical signal and, based on the morphology match scores, withholds detection of a tachyarrhythmia episode. In some examples, the ICD detects T-wave oversensing based on the morphology match scores and withholds detection of a tachyarrhythmia episode in response to detecting the T-wave oversensing.