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.

Brugada syndrome and related forms of ion channelopathies, including ventricular asynchrony of contraction, originate in the region near the His bundle or para-Hisian regions of the heart. Manifestations of Brugada syndrome can be corrected by delivering endocardial electrical stimulation coincident to the activation wave front propagated from the atrioventricular (AV) node early enough to compensate for the conduction problems that start in those region. The stimulation can include waveforms of the same or different polarity delivered to a site within the region near the His bundle or para-Hisian regions of the heart associated with a low cardiac electrical asynchrony level or can include at least two single-phased superimposed waveforms of opposite polarity delivered through a pair of pacing electrodes relative to a reference electrode, which can be delivered to any site within the region near the His bundle or para-Hisian regions of the heart.

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.

Methods and systems methods for continuously monitoring a patient for cardiac electrical abnormalities including atrial fibrillation, asystole, ventricular fibrillation and tachycardia.

A heartrate monitor detects heartbeats in a test signal. A local heartrate and an energy of acceleration are associated with the detected heartbeats. Detected heartbeats are included or excluded from a test set of heartbeats based on the local heartrate and energy of acceleration associated with the respective heartbeats. Anomalous heartbeats in the test set of heartbeats are detected using a sparse approximation model. The heartrate monitor may detect heartbeats in a training heartbeat signal. A reference heart rate and an energy of acceleration are associated with detected beats of the training heartbeat signal and selectively included in a set of training data based on the heart rate and energy of acceleration associated with the detected beat in the training heartbeat signal. A dictionary of the sparse representation model may be generated using the set of training data.

A method includes obtaining a filtered waveform signal, marking the waveform signal as K signal line segments based on monotonicity, extracting line segment data of each signal line segment, and determining a line segment matching template of the waveform signal based on the line segment data of each signal line segment, where the line segment matching template includes M consecutive signal line segments, and M is an integer less than K. The method further includes matching each of the K signal line segments with the M signal line segments included in the line segment matching template, and determining a target wave group of the waveform signal based on a matching result of each signal line segment. The method further includes determining periodic signal data of the waveform signal based on line segment data of the target wave group.

Techniques are provided for generating and processing compressed sensor data. Sensor signals can be collected using one or more sensors. The sensor signals can be compressed using a compression data structure. In some instances, the compressed signal corresponds to a sampling rate at or below the Nyquist sampling rate. The compressed signal can be compared to one or more templates. Events within the compressed signal can be detected and characterized based on the comparison.

A handheld device measures all vital signs and some hemodynamic parameters from the human body and transmits measured information wirelessly to a web-based system, where the information can be analyzed by a clinician to help diagnose a patient. The system utilizes our discovery that bio-impedance signals used to determine vital signs and hemodynamic parameters can be measured over a conduction pathway extending from the patient's wrist to a location on their thoracic cavity, e.g. their chest or navel. The device's form factor can include re-usable electrode materials to reduce costs. Measurements made by the handheld device, which use the belly button as a fiducial marker, facilitate consistent, daily measurements, thereby reducing positioning errors that reduce accuracy of standard impedance measurements. In this and other ways, the handheld device provides an effective tool for characterizing patients with chronic diseases, such as heart failure, renal disease, and hypertension.

An endovascular navigation system and method are disclosed. The endovascular navigation system includes an elongate flexible member configured to access the venous vasculature of a patient, a processor, and a display. The elongate flexible member includes an endovascular electrogram lead disposed at a distal end of the elongate flexible member and configured to sense an endovascular electrogram signal of the venous vasculature of the patient, and a first wireless interface configured to wirelessly transmit the endovascular electrogram signal to the processor. The processor includes a second wireless interface configured to wirelessly receive the endovascular electrogram signal from the elongate flexible member. The processor is configured to determine that the position of the distal end of the elongate flexible member is within a predetermined structure within the venous vasculature of the patient. The display is configured to display a visual indication that the distal end of the elongate flexible member is within the predetermined structure within the venous vasculature of the patient.

A method for non-invasive detection of coronary artery disease (CAD). The method includes acquiring a raw ECG signal from a patient, generating a denoised ECG signal by applying a first wavelet transform on the raw ECG signal, generating an artifact-free ECG signal by applying a second wavelet transform on the denoised ECG signal, generating a filtered ECG signal by applying a band-stop filter on the artifact-free ECG signal, extracting an averaged ECG signal of a plurality of averaged ECG signals from the filtered ECG signal, detecting an ST segment in the averaged ECG signal by applying a delineation algorithm on the averaged ECG signal, detecting an isoelectric line in the averaged ECG signal, determining an existence of CAD in the patient responsive to detecting a CAD detection condition, and determining a non-existence of CAD responsive to not detecting the CAD detection condition.