42 results about "EEG HYPSARRHYTHMIA" patented technology

What is disclosed is a system and method for processing a time-series signal generated by video images captured of a subject of interest in a non-contact, remote sensing environment such that the existence of a cardiac arrhythmia can be determined for that subject. In one embodiment, a time-series signal generated is received. The time-series signal was generated from video images captured of a region of exposed skin where photoplethysmographic (PPG) signals of a subject of interest can be registered. Signal separation is performed on the time-series signal to extract a photoplethysmographic signal for the subject. Peak-to-peak pulse points are detected in the PPG signal using an adaptive threshold technique with successive thresholds being based on variations detected in previous magnitudes of the pulse peaks. The pulse points are then analyzed to obtain peak-to-peak pulse dynamics. The existence of cardiac arrhythmias is determined for the subject based on the pulse dynamics.

In some embodiments, a wearable cardioverter defibrillator (“WCD”) system may output an opening human-perceptible indication, after detecting a shockable cardiac arrhythmia but before validating it. This may succeed in informing the patient that the WCD system is working, and in particular analyzing a just-detected cardiac arrhythmia. The information may give comfort and confidence to the patient who may be conscious, and be experiencing only ventricular tachycardia but not ventricular fibrillation.

Techniques for predicting cardiac arrhythmia includes obtaining first data that indicates an electrocardiography recording from a patient; and, automatically deriving, on a processor, P-wave characteristics on a plurality of leads of the electrocardiography recording. A value for a first parameter, Pindex3, is determined based on a standard deviation of P-wave duraations automatically derived from only three leads of the plurality of leads. A risk of incidence of cardiac arrhythmia for the patient is determined based, at least in part, on the first parameter, Pindex3.

A cardiac contractility modulating (CCM) device (30) includes an anti-arrhythmic therapy unit (38) for detecting a cardiac arrhythmia in a heart (2) of a patient based on processing electrical signals related to cardiac activity sensed at the heart, and for delivering anti-arrhythmic therapy to the heart. The device includes a cardiac contractility modulating (CCM) unit (40) capable of delivering cardiac contractility modulating (CCM) signals to the heart for modulating the contractility of a portion of the heart. The device (30) includes a power source (165). The device may be an implantable device or a non-implantable device. A method for delivering anti-arrhythmic therapy to a heart. The method includes applying one or more non-excitatory cardiac contractility modulating electrical signals to said heart.

A method and system for predicting the onset of heart arrhythmias more accurately observes trends in abnormal or pathologic morphology of the electrocardiogram (ECG). A first set of ECG signals is monitored from a patient. A baseline measurement is generated from the monitored first set of ECG signals to contain nonpathologic ECG morphologies in each lead. A second set of ECG signals is monitored from the patient and the baseline measurement is subtracted from the second set of ECG signals on a beat-to-beat basis. Afterwards, a residuum signal is generated for each lead based on the subtraction. R-wave heterogeneity, T-wave heterogeneity, P-wave heterogeneity, or ST-segment heterogeneity or other indicators of arrhythmia risk or myocardial ischemia are quantified based on the generated residuum signals.

Systems and methods for assessing hemodynamic status of a patient experiencing atrial tachyarrhythmia such as an atrial fibrillation (AF) episode are disclosed. A system can comprise an atrial tachyarrhythmia detection circuit configured to detect an AF episode, a hemodynamic sensor circuit configured to sense at least one hemodynamic signal, and a hemodynamic status analyzer circuit that can calculate one or more signal metrics using the sensed hemodynamic signal during the AF episode. The hemodynamic status analyzer circuit can categorize the hemodynamic status of the patient into one of two or more categorical hemodynamic status levels which indicate elevated hemodynamic impact of the detected AF episode. A user interface can provide to an end-user a presentation of the categorized hemodynamic status level during AF.

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.

The present invention relates to generating hiPSC-derived cardiomyocytes and embryoid bodies that recapitulate the disease phenotype of Long QT Syndrome and their use in developing pharmacological treatments thereof. The present invention also includes the use of a compound which inhibits the ubiquitin-proteasome pathway for the preparation of a medicament for the prophylaxis or treatment of a disease associated with prolonged ventricular repolarization (cardiac arrhythmia) caused by one or more mutations in the amino acid sequence of the hERG potassium channel.

The invention discloses a design method for a heart failure model of a human ventricular muscle tissue, and belongs to the technical field of virtual human hearts. Heart failure is taken as a research object, and myocardial electrophysiological and mechanics characteristics and a spiral wave dynamics mechanism under heart excitation-contraction coupling are discussed to discover a relationship of interaction between the heart failure and arrhythmia. A TP06 model simulates a single ventricular muscle cell of a human body, then the TP06 model is coupled to an NHS08 model, and an ECC model is built; based on an improved TP06 model and existing data, a human ventricular heart failure muscle cell model is built, and the electrophysiological and mechanics characteristics of human ventricular muscle cells, an action potential duration restitution curve and an early afterdepolarization restitution curve under normal and heart failure conditions are compared; finally by adding coupling among the cells, a two-dimensional single-layer myocardial tissue action potential conduction model is successfully built, and spiral waves are induced by adopting a ''wave shearing method''; and then, dynamics characteristics of the spiral waves under the normal and heart failure conditions are compared.