Disclosed herein are methods, systems, and apparatus for treating a medical condition of a patient, involving detecting a physiological cycle or cycles of the patient and applying an electrical signal to a portion of the patient's vagus nerve through an electrode at a selected point in the physiological cycle(s). The physiological cycle can be the cardiac and/or respiratory cycle. The selected point can be a point in the cardiac cycle correlated with increased afferent conduction on the vagus nerve, such as a point from about 10 msec to about 800 msec after an R-wave of the patient's ECG, optionally during inspiration by the patient. The selected point can be a point in the cardiac cycle when said applying increases heart rate variability, such as a point from about 10 msec to about 800 msec after an R-wave of the patient's ECG, optionally during expiration by the patient.

There is provided a computer-implemented method for identifying abnormal QRS-complexes in an ECG signal comprising: receiving an ECG signal with detected QRS-complexes; calculating and normalizing a plurality of geometric measures of the QRS-complexes; constructing an RGB image with three two-dimensional matrices, each matrix corresponding to one of the calculated plurality of geometric measures, the geometric measures belonging to one QRS-complex have the same matrix index across the three two-dimensional matrices; transforming the RGB image to a plurality of gray-scale images; computing histograms of each of the plurality of gray-scale image; iteratively comparing every histogram peak to its previous one; and marking pixel intensities corresponding to histogram peaks with a difference value of equal or greater than a predefined threshold referred to as a saliency threshold, as salient pixels; using saliency detection for mapping salient pixels indices onto the ECG signal and classifying the salient pixel indices as abnormal QRS complexes.

The present disclosure describes various systems and methods of modifying a display to automatically visually trace an abnormality associated with a physiological signal received from a patient (i.e., subject). In particular aspects, the systems and methods described herein utilize three-dimensional display outputs of physiological signals that allow for the immediate differentiation between normal portions of the physiological signal and abnormal portions of the physiological signal.

An monitor includes a host and a first display communicatively connected to the host. In a display screen switching method for the monitor, it is detected that a second display is connected, the second display is provided independently of the monitor. It is detected that a display screen switching instruction is received and a display file corresponding to configuration parameters of the second display is read, the display file includes one or more physiological parameters to be displayed, an interface layout and interface elements. Data of the one or more physiological parameters are acquired according to the display file and generating frame data for representing pixel values of pixels on a display interface. The frame data are output to the second display to display data of the one or more physiological parameters.

A system for out of band control for legacy set top boxes.

A medical device is configured to deliver anti-tachycardia pacing (ATP) in the presence of T-wave alternans. The device is configured to detect a ventricular tachyarrhythmia from a cardiac electrical signal received by the medical device. In response to the detected ventricular tachyarrhythmia, the device delivers a plurality of ATP pulses at alternating time intervals. The alternating time intervals comprise at least a first ATP time interval separating a first pair of the ATP pulses and a second ATP time interval different than the first ATP time interval. The second ATP time interval consecutively follows the first ATP time interval and separates a second pair of the ATP pulses.

Computer implemented methods and systems for monitoring cardiac activity (CA) signals, for a series of beats, over first and second sensing channels having different first and second detection thresholds, respectively. The methods and systems also include analyzing the CA signals over the first and second sensing channels utilizing the first and second detection thresholds, respectively, during an event prediction window to detect a presence of sensed events. The methods and systems also include determining amplitudes of the sensed events detected. The methods and systems also include calculating at least one of an amplitude distribution or amplitude trend for the sensed events detected over the first and second channels and adjusting at least one of the first or second detection thresholds based on the at least one of the amplitude distribution or amplitude trend.

Computer implemented methods and systems for monitoring cardiac activity (CA) signals, for a series of beats, over first and second sensing channels having different first and second detection thresholds, respectively. The methods and systems also include analyzing the CA signals over the first and second sensing channels utilizing the first and second detection thresholds, respectively, during an event prediction window to detect a presence of sensed events. The methods and systems also include determining amplitudes of the sensed events detected. The methods and systems also include calculating at least one of an amplitude distribution or amplitude trend for the sensed events detected over the first and second channels and adjusting at least one of the first or second detection thresholds based on the at least one of the amplitude distribution or amplitude trend.

A method includes analyzing a first segment of electrocardiogram measurements corresponding to a first heartbeat and a second heartbeat of a patient to identify a set of features of the first segment of electrocardiogram measurements. The method further includes adjusting the set of features based at least on the first segment and a second segment of electrocardiogram measurements corresponding to the first heartbeat. The method further includes predicting, based on the adjusted set of features, a region in the second segment of electrocardiogram measurements comprising a p-wave generated by the second heartbeat.

Described herein is a computer implemented method of measuring the determining the Left Ventricular Ejection Fraction (LVEF) of a patient. The S Wave, P Wave, R Wave and T Wave are continually measured using an ECG apparatus. The LVEF is computed as a function of S Wave, P Wave, R Wave and T Wave. The system described herein includes an ECG apparatus and an analytical computing device for computing the LVEF.