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1.
Article in English | MEDLINE | ID: mdl-18001943

ABSTRACT

Although atrial fibrillation is the most common sustained cardiac rhythm disturbance, it remains under-diagnosed. One of the most drastic complications is embolism, and strokes in particular. Patients having atrial fibrillation must be identified in order to reduce the number of strokes. The algorithm presented detects atrial fibrillation, even without it being indicated in the analyzed ECG. Based on parameters of heart rate variability, only a 60-minute single channel ECG is required. At first, all R peaks are detected and all RR intervals are calculated. After normalizing the RR intervals, the time domain parameter SDSD is calculated and the so-called Poincaré Plot is generated. The image and the time domain analysis assess a risk level, which determines whether the patient is suffering from atrial fibrillation. The resulting sensitivity calculated for ECG recordings from the MIT-BIH Atrial Fibrillation Database is 91.5% and the specificity determined for the ECG recordings from the MIT-BIH Normal Sinus Rhythm Database is 96.9%. The sensitivity depends on the atrial fibrillation burden. Even if a burden of 0 % is assumed, the results still prove satisfactory (sensitivity nearly 83%).


Subject(s)
Algorithms , Atrial Fibrillation/diagnosis , Electrocardiography/methods , Atrial Fibrillation/physiopathology , Heart Rate/physiology , Humans , Sensitivity and Specificity
2.
Article in English | MEDLINE | ID: mdl-18002799

ABSTRACT

The most frequently occurring cardiac arrhythmia in the adulthood is atrial fibrillation. In Germany, the number of sick people is estimated at 800,000. Patients who suffer from atrial fibrillation often do not sense any symptoms of the illness. Through the uncontrolled blood flow in the atrium, a blood clot, which can lead to the blood circulation for an embolism or for a stroke, can form itself. These persons must be recognized, because of their increased stroke risk in order to be able to attend it. In this work, the chest strap CorBelt, developed by the company Corscience GmbH&Co.KG, is equipped with an algorithm for the recognition of atrial fibrillation with the aid of heart rate variability.


Subject(s)
Algorithms , Atrial Fibrillation/diagnosis , Brain Ischemia/prevention & control , Diagnosis, Computer-Assisted/instrumentation , Electrocardiography, Ambulatory/instrumentation , Stroke/prevention & control , Telemetry/instrumentation , Atrial Fibrillation/complications , Brain Ischemia/diagnosis , Diagnosis, Computer-Assisted/methods , Electrocardiography, Ambulatory/methods , Equipment Design , Equipment Failure Analysis , Humans , Mass Screening/instrumentation , Mass Screening/methods , Stroke/diagnosis , Telemetry/methods
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