A real‐time feature extraction method for PVC detection in bedside monitor
- 1 July 1987
- journal article
- research article
- Published by Taylor & Francis in Journal of the Chinese Institute of Engineers
- Vol. 10 (5) , 511-516
- https://doi.org/10.1080/02533839.1987.9677004
Abstract
This paper describes a fast and very efficient feature extraction method for discrimination of QRS and Premature Ventricular Contraction (PVC) beats in a microprocessor‐based bedside monitoring system. It converts each QRS and PVC beat into a positive‐pulse waveform by signal preprocessing. Two characteristic factors, the positive‐pulse and the pulse duration, are calculated when the onset and end points of each pulse have been detected by threshold detection. The prominent feature is extracted from a product of these two factors. This algorithm has been examined using 40 different patients’ electrocardiograph (ECG). The accuracy of QRS detection was 99.3 percent in the tests performed. The identification sensitivity of PVC was 81.2 percent with 18‐ different arrhythmia patients.Keywords
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