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A Rule-Based Classification of ECG Rhythms Using Moving First Derivative of the Signal
Preview AbstractThe rhythm of a scanned ECG paper can be interpreted by extracting the first derivative of the signal. This paper discusses a first derivative method to classify five different rhythms, namely: Normal Sinus Rhythm, Sinus Bradycardia, 1st Degree AV Block, Atrial Flutter and the Asystole. The PQRST Wave complex is mapped and the different intervals are identified. Unlike other methods where learning is needed and quite a number of data are required, the method described here used rule-based method. It is capable of interpreting data with minimal samples. Based on the studied data, the method was able to produce a 95% accuracy for samples with grids that do not perfectly lie in time axis.