An algorithm for extraction of ECG features is presented. Digital filters and adaptive thresholds are used for the QRS detection and Chebyshev polynomial approximation is used for QRS shape recognition. The performance of the algorithm is evaluated discussed. The algorithm will be used for monitoring patients in intensive care unit, however future work is required.
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This paper describes a way to mode! ECG signals that is used for building and testing an automated arrhythmia analyzer. The segments of the waveform are approximated by Gaussian curves, which is simple and generates realistic-looking waveforms- By modeling subsequent heartbeats it is possible to obtain the ECG's of every arrhythmia. The signals generated may be comfortably used for designing an automated ECG analyzer and for leaching medicine students.
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