Key result
A signal processing correlation technique achieved 100% accuracy in identifying normal versus abnormal ECGs (arrhythmias) in Indian patients.
A simple cross-correlation technique using MATLAB can accurately distinguish normal from abnormal ECGs in digitized paper records, potentially aiding automated diagnosis in resource-limited settings.
The paper proposes a method based on signal processing correlation technique to find out whether the ECG is normal or abnormal. Many of the abnormal ECGs are called Arrhythmias. ECG (lead II) obtained from conventional ECG machine of Indian patients are digitized and the data are crosscorrelated with the reference standard normal ECG data. Two different beats of the same ECG data are also correlated. The correlation parameters are used to identify the ECG as normal or abnormal. The accuracy obtained in this method is 100%. The cross-correlation is done using MATLAB 7.12.0 (R2011a) tools.
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Ayub et al. (2012) studied Arrhythmias. Signal processing correlation technique vs. Reference standard normal ECG data was evaluated on Accuracy of identifying ECG as normal or abnormal. A signal processing correlation technique achieved 100% accuracy in identifying normal versus abnormal ECGs (arrhythmias) in Indian patients.
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