It is found in this research to adopt a new classifier for diagnosing
Cardiac Arrhythmias depending on detecting the Electrocardiograph (ECG),
where the classifier can identify heart beats and extract its features. Using
these features we can deci
de if the heart beat is healthy or disordered.
Beside detection normal heart beats, the research focused on detection
two diseases:
1. Premature Ventricular Contraction PVC.
2. Premature Atrial Contraction PAC.
The new classifier diagnosed the two diseases with a very high quality
where the accuracy average is 97.56%.
The new classifier is developed depending on algorithms of ANFIS
Adaptive Neural Fuzzy Inference System. System includes two consecutive
neural networks; first one sorts the heart beats to two types: normal and
abnormal were the second diagnose the disease of the disordered heartbeats
only.
This new classifier offered higher levels of efficiency and accuracy in
the comparison with the internationally known classifiers.
