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- W2098894658 abstract "In this paper, a real-time QRS beat classification system devised based on a nonlinear trimmed moving averaging filter is presented. Such a nonlinear system aims to identify the abnormal beat of ventricular origin from the normal one. The proposed beat classifier can function in parallel with a real-time QRS detector, permitting the tasks of beat detection and diagnosis to alternate with each other. Algorithm performance was evaluated against the ECG recordings selected from the MIT-BIH arrhythmia database. Numerical results demonstrated that over 99.8% beat identification rate can be achieved by the algorithm." @default.
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- W2098894658 date "2003-01-01" @default.
- W2098894658 modified "2023-09-23" @default.
- W2098894658 title "Development of a real-time QRS beat classifier using a nonlinear trimmed moving averaging-based system" @default.
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- W2098894658 doi "https://doi.org/10.1109/cic.2003.1291221" @default.
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