Devices and methods for dynamically controlling sensitivity associated with detecting R-waves while maintaining the fixed detection threshold are described herein. One such method includes sensing an analog signal indicative of cardiac electrical activity, converting the analog signal indicative of cardiac electrical activity to a digital signal indicative of cardiac electrical activity, and detecting R-waves by comparing the digital signal indicative of cardiac electrical activity to a fixed detection threshold to thereby detect threshold crossings that corresponds to R-waves. The method further includes selectively adjusting a gain applied to the digital signal indicative of cardiac electrical activity to thereby selectively adjust a sensitivity associated with the detecting R-waves, while maintaining the fixed detection threshold.

An ECG system measures and annotates a subdivision of the P wave of the ECG waveform from harmonic waveforms. Electrical impulses are received from a beating heart. The electrical impulses are converted to an ECG waveform. The ECG waveform is converted to a frequency domain waveform, which, in turn, is separated into two or more different frequency domain waveforms, which, in turn, are converted into a plurality of time domain cardiac electrophysiological subwaveforms and discontinuity points between these subwaveforms. The plurality of subwaveforms and discontinuity points are compared to a database of subwaveforms and discontinuity points for normal and abnormal patients. Starting and ending discontinuity points are identified for a subdivision of the P wave of the ECG waveform and an APD is calculated for the subdivision. The ECG waveform is displayed along with a location of the P wave subdivision on the ECG waveform and the calculated APD.

Systems, apparatus, and methods for ablation therapy are described herein, with a processor for confirming pacing capture or detecting ectopic beats. An apparatus includes a processor for receiving cardiac signal data captured by a set of electrodes, extracting a sliding window of the cardiac signal data, identifying a peak frequency over a subrange of frequencies associated with the extracted sliding window, detecting ectopic activity based at least on a measure of the peak frequency over the subrange of frequencies, in response to detecting ectopic activity, sending an indication of ectopic activity to a signal generator configured to generate pulsed waveforms for cardiac ablation such that the signal generator is deactivated or switched off from generating the pulsed waveforms. An apparatus can further include a processor for confirming pacing capture of the set of pacing pulses based on cardiac signal data.

A computer-implemented method, computer program product and computing system for receiving a single-lead heartbeat waveform for a user; associating a heart health indicator with the single-lead heartbeat waveform; and providing the heart health indicator to a recipient.

A computer-implemented method, computer program product and computing system for receiving a single-lead heartbeat waveform for a user obtained via a differential voltage potential measurement concerning the heart of the user; associating a heart health indicator with the single-lead heartbeat waveform; and providing the heart health indicator to the user.

The exemplary systems and methods may be configured to monitor electrical activity from a patient using a plurality of external electrodes. The exemplary systems and methods may be further configured to provide a model heart representative of the patient's heart based on at least one of a plurality of patient characteristics. The model heart can include a plurality of segments. The exemplary systems and methods may be further configured to determine a value of electrical activity for each of a plurality of anatomic regions of the model heart based on the mapped electrical activity. Each of the plurality of anatomic regions can include a subset of the plurality of segments.

Methods and systems for detecting and diagnosing sleep apnea include using three lead electrocardiogram (ECG) monitoring devices to calculate ECG derived respiration data. Beat-typing information from the ECG device's analyser is used to enhance the derived respiration data by removing beats identified as non-normal. Surrounding epoch information is integrated early and epoch posterior probabilities are thresholded in order to remove diffident epochs. The system is further trained as new data is collected in the database.

A heart-rate associated with a heartbeat signal is determined. A transform is selected based on the determined heart-rate associated with the heartbeat signal and a reference heart-rate associated with a dictionary of a sparse approximation model. The transform is selected independent of other factors associated with generation of the heartbeat signal. The selected transform is applied to the dictionary of the sparse approximation model, generating an adjusted dictionary of the sparse approximation model. Anomalous heartbeats in the heartbeat signal are detected using the adjusted dictionary of the sparse approximation model.

Described herein are methods, software, systems and devices for detecting the presence of an abnormality in an organ, tissue, body, or portion thereof of a subject by analysis of the electromagnetic fields generated by the organ, tissue, body, or portion thereof.

A system for reporting cardiologic data includes a patient-portable monitoring device and circuitry. The monitoring device is configured to detect electrocardiogram (ECG) data and patient-initiated event data. The circuitry is configured to receive the ECG data and the patient-initiated event data; detect atrial fibrillation (AF) events in the ECG data; calculate the duration of each AF event by subtracting the respective start time from the respective stop time of each AF event; compare the duration of each AF event to a first duration threshold; store each AF event having a duration exceeding the first duration threshold; calculate a monitoring time period duration by subtracting the monitoring start time from the monitoring stop time; calculate, based on the stored AF events, AF burden; and output a graphical presentation of the patient-initiated event data, AF burden, and stored AF events. The first duration threshold is less than 30 seconds.