87 results about "Sinus rhythm" patented technology

A heart monitor for use as a non-invasive screening tool for identifying potential atrial fibrillation in patients comprises a sensor for producing an output waveform of the patient's actual sinus rhythm, a processing unit arranged to store the normalised waveform of an ideal sinus rhythm and to compare the actual and ideal sinus rhythm waveforms and to produce an output dependant on the difference on a display. The value of the output is indicative of whether the patient is atrial fibrillation or other cardiac arrhythmia.

An arrhythmia discrimination device and method involves receiving electrocardiogram signals and non-electrophysiologic signals at subcutaneous locations. Both the electrocardiogram-signals and non-electrophysiologic signals are used to discriminate between normal sinus rhythm and an arrhythmia. An arrhythmia may be detected using electrocardiogram signals, and verified using the non-electrophysiologic signals. A detection window may be initiated in response to receiving the electrocardiogram signal, and used to determine whether the non-electrophysiologic signal is received at a time falling within the detection window. Heart rates may be computed based on both the electrocardiogram signals and non-electrophysiologic signals. The rates may be used to discriminate between normal sinus rhythm and arrhythmia, and used to determining absence of an arrhythmia.

Apparatus is provided, which includes an electrode device, configured to be coupled to an atrial site of a subject containing parasympathetic nervous tissue, and a control unit. The control unit is configured to, responsively to a detection of an episode of non-sinus atrial tachycardia, restore normal sinus rhythm (NSR) of the subject, by driving the electrode device to apply a parasympathetic stimulation signal to the atrial site, and configuring the parasympathetic stimulation signal to activate the parasympathetic nervous tissue sufficiently to restore the NSR. Other embodiments are also described.

A method of determining a confidence level in a heart rate obtained from an ECG signal of a patent comprises determining a heart rate from a segment of an ECG signal, the segment having a pre-determined length, and determining a first confidence level in the determined heart rate. If the first confidence level exceeds a predetermined value, the heart rate is output. Otherwise, the method further comprises determining a set of features from the segment of the ECG signal; and classifying the segment of the ECG signal, based on one or more features selected from the determined set of features and the heart rate, into one of at least three classes: noise, an abnormal sinus rhythm and a normal sinus rhythm.

A method for accurate and rapid automated detection of atrial fibrillation (AF), sinus rhythm (SF), and atrial flutter (AFL) is disclosed, which allows distinguishing of these cardiac signals with lowered risk of errors by implanted pacemakers and like devices. The method includes training episodes of intra-cardiac signals (called the closed data set CDS) to evaluate five feature parameters with a discriminator classifying the signal into AF, AFL or sinus rhythm (SR). Comparison with the independent decisions of experienced physicians for each episode reveals specificity, accuracy and sensitivity of greater than 97%. Each episode is a window of intracardiac signal of interval 1-2 seconds with the discriminator providing results in less than 0.25 s. In another aspect, the method is resistant to the presence of noise in the data. In yet another aspect, more feature parameters may be used in alternative implementations including for detecting signals other than AF, AFL & SR.

An implantable medical device is provided that comprises a housing, sensors configured to be located to proximate a heart, and a sensing module to sense cardiac signals originating from the heart over a channel defined by the sensors. The cardiac signals include intrinsic R-wave events and associated intrinsic confirmation events when the heart exhibits normal sinus rhythm. The device further includes memory to store the cardiac signals sensed over a channel, and a detection module. The detection module identifies an R-wave event within the cardiac signals. The detection module captures, in the memory, a segment of the cardiac signals that precedes the R-wave event as a retrospective segment. The detection module determines whether the retrospective segment includes an intrinsic confirmation event that is associated with and occurs before the R-wave event. The detection module declares an arrhythmia based at least in part on the determination of whether the retrospective segment includes the intrinsic confirmation event is absent from the retrospective segment.

An implantable cardioverter/defibrillator includes a tachycardia detection system that detects one-to-one (1:1) tachycardia, which is a tachycardia with a one-to-one relationship between atrial and ventricular contractions. When the 1:1 tachycardia is detected, the system discriminates ventricular tachycardia (VT) from supraventricular tachycardia (SVT) based on analysis of a cardiac time interval. Examples of the cardiac time interval include an atrioventricular interval (AVI) and a ventriculoatrial interval (VAI). A template time interval is created during a known normal sinus rhythm. The system measures a tachycardia time interval after detecting the 1:1 tachycardia, and indicates a VT detection if the tachycardia time interval differs from the template time interval by at least a predetermined percentage of the template time interval.

While detecting a cardiac arrhythmia, a mapping electrode of a probe is used to associate a local activation time with a first location in a region of interest in the heart. While detecting an absence of the cardiac arrhythmia, the local activation time is associated with a second location in the heart. Electrical data of the first location is assigned to the second location, and an electroanatomic map of the heart is generated that includes the second location in association with the assigned electrical data of the first location.

Improved methods and devices perform anti-tachycardia pacing (ATP) to convert a ventricular tachycardia (VT) to normal sinus rhythm. In one embodiment of the invention bi-ventricular (BV) ATP is employed. In this embodiment the right ventricle and left ventricle of a patient's heart are independently paced based on signals sensed in each chamber.

The invention discloses a method for obtaining an artificial neural network weighted value matrix for identifying atrial fibrillation. The method includes the steps of calling an MIT-BIH arrhythmia database, an MIT-BIH normal sinus rhythm database and a long-time atrial fibrillation database as trainning samples, introducing an artificial neural network for learning training, randomly setting the weighted value of each layer of artificial neural network, and inputting training data samples to conduct repeated iteration to correct the weighted value of each layer until the training error is smaller than a designated value. In this way, the weighted value matrix for determining occurrence of atrial fibrillation can be found, the weighted value matrix is added into an original artificial neural network to establish a new artificial neural network, and human electrocardiosignals are processed with the acquired target human electrocardiosignals as data to obtain a target human body characteristic vector X. The prediction operation is carried out according to the target human body characteristic vector X and the new artificial neural network.

The invention relates to a method, a device, electronic equipment and a storage medium for electrocardiogram signal detection and classification. The method comprises the following steps of: extracting a signal waveform from an electrocardiogram signal; acquiring a morphological characteristic and a deep characteristic of the signal waveform, wherein the morphological characteristic comprises anyone of a TR wave amplitude difference characteristic, a PR wave quantity ratio characteristic, an ST wave band characteristic and a P wave variation characteristic, and the deep characteristic comprises a depth characteristic and a hierarchy characteristic; inputting the morphological characteristic and the deep characteristic into a classifier; and acquiring a classification result output by theclassifier so as to obtain the signal type of the electrocardiogram signal, wherein the classification result is a result that the classifier performs classification according to the morphological characteristic and the deep characteristic, and the signal type comprises an atrial fibrillation rhythm, a non-atrial fibrillation abnormal rhythm, a normal sinus rhythm and noise. The method can accurately identify various types of abnormal rhythms, avoids the situation that abnormal rhythms of non-atrial fibrillation types such as tachycardia, bradycardia and arrhythmia are classified into atrial fibrillation types in error, and improves the accuracy of classification of electrocardiogram signals.

A new method for curative radiofrequency AF ablation to achieve the inactivation or distruction of fibrillar myocarcium and of the AF nests. In addition, evidence that fibrillar myocardium could be of the real AF substratum was found. Identified and mapped by spectral analysis and phase study of the tissue, which seems to have intermediate features between nervous and myocardium. The procedure by transeptal puncture which requires only one catheter for ablation and mapping. The new method may be localize the application targets even during arrhythmia.

A SubQ ICD that is entirely implantable subcutaneously with minimal surgical intrusion into the body of the patient and associated with subcutaneous leads provides distributed cardioversion-defibrillation sense and stimulation electrodes for delivery of cardioversion-defibrillation shock and pacing therapies across the heart when necessary. A level crossing detection system and process is implemented to detect noise, sinus rhythm and ventricular fibrillation in subcutaneous or body surface signals to deliver therapies as needed.

Vagal stimulation applied to the atrioventricular nodal (“AVN”) fat pad and the sinoatrial nodal (“SAN”) fat pad via epicardial leads is useful for controlling cardiac arrhythmia, including atrial fibrillation (‘AF”). In the case of AF, for example, vagal stimulation may be applied initially to the AVN fat pad to reduce ventricular rate, and vagal stimulation may be applied to the SAN fat pad after restoration of sinus rhythm to control atrial rate. The technique is applicable to control acute AF and chronic AF. The vagal stimulation may be optimized for exciting ganglia in the fat pads to produce dromotropic and chronotropic effects in the atrioventricular node and the sinoatrial node, respectively. In addition, the SAN fat lead can also be used to pace the atrium in case of sinus bradycardia.

The invention relates to an atrial fibrillation detection method and system. A condition that whether signals have P wave or not is added while the characteristic reflecting RR interval irregularity of the ECG signals is extracted, so that the problem of false detection of sinus arrhythmia signals is solved; a BP neural network method is adopted to replace simple logic conditions to judge atrial fibrillation signals, so that atrial fibrillation detecting accuracy when input RR interval number is small is improved.

A combination cardiac stimulator for CRT stimulation and CCM stimulation, which is connected to a rhythm evaluation unit which can either detect a sinus rhythm that is present, or classify an atrial arrhythmia, and which comprises an additional therapy selection unit, wherein the therapy selection unit selects the delivery of either CRT therapy or CCM therapy on the basis of the classification of the atrial rhythm such that CRT therapy is preferred in the case of sinus rhythm, and CCM therapy is delivered in the case of atrial arrhythmia.