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69 results about "Ventricular rate" patented technology

Most normal heart rates are in the range of 60 to 100 beats a minute. Ventricular tachycardia can result in rates as high as 170 beats a minute or even more.

Method and apparatus for using atrial discrimination algorithms to determine optimal pacing therapy and therapy timing

A system and method which employs atrial discrimination algorithms to distinguish between different atrial arrhythmias occurring in a patient for selecting an optimal pacing therapy corresponding to the type of arrhythmia identified. The invention may be implemented in a bradycardia pacemaker or other implantable cardiac device. In response to the detection of an atrial rate above the atrial tracking rate, discrimination criteria are applied to a detected atrial activity signal to distinguish between different types of supraventricular tachycardia, such as fast atrial flutter and other atrial flutter at a relatively slower rate, which may be occurring in the patient. The discrimination criteria may be, for example, rate-based or morphology based. The pacer is controlled to provide pacing therapy to a heart in a manner corresponding to the type of supraventricular tachycardia identified. For example, antitachycardia pacing may be provided to the heart in response to the detection of a relatively lower rate supraventricular tachycardia / other atrial flutter, whereas another pacing control, e.g., ventricular pacing, such as ventricular rate regulation or Rate Smoothing, may be applied if a more rapid rate supraventricular tachycardia / fast atrial flutter is identified. The output of an atrial discrimination algorithm may be tracked and the trend thereof used to improve therapy timing.
Owner:CARDIAC PACEMAKERS INC

Intelligent electrocardiogram data classification method based on voting ensemble learning

An intelligent electrocardiogram data classification method based on voting ensemble learning in the invention is characterized by being realized through the following steps: a) carrying out data preprocessing; b) establishing a logistic regression model; c) establishing a decision tree model; d) establishing a support vector machine; e) establishing a naive Bayesian model; f) establishing a neuron model; g) establishing a k proximity model; and h) carrying out model integration. Finally, a model with the accuracy of not less than 80% is obtained, and the effect of the model is better than theeffect of the single model established in the steps b) to g). According to the intelligent electrocardiogram data classification method, enough data are firstly acquired from ccdd and are divided into a training set and a test set, then various models are established, and the model with accuracy of not less than 80% is finally obtained, thereby realizing intelligent identification and classification of normal, atrial fibrillation, atrial premature beat, accidental atrial premature beat, frequent atrial premature beat, atrial tachycardia and atrial fibrillation accompanied with rapid ventricular rate, and realizing early discovery and early treatment of cardiovascular diseases.
Owner:SHANDONG COMP SCI CENTNAT SUPERCOMP CENT IN JINAN
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