Cardiac Abnormalities Detection from Compressed ECG

Miguel Torres-Cisneros, Rafael Guzman Cabrera, S. Villalobos, Daniel Alberto May-Arrioja, F. Martell


In the aim of automatic detection of cardiac anomalies, in particular arrhythmias, we propose and design two algorithms for arrhythmias detection based on the energy of the ECG signal. Our results have shown that it is possible to obtain a prediction error as small as 0.66% when we use the overlapped windows method. Our algorithms can obtain this error analyzing 30 min signal length just in 12 s of processing time. Our results are faster and competitive if we compare them with those in the literature.


ECG automatic detection, QRS complex detection, RR segment

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