Key result
A new fast Fourier transform-based algorithm was developed and verified to accurately classify normal and abnormal ECG waveforms for automatic computerized interpretation.
Why the study?
Development of automatic and computerized ECG interpretation and diagnosis requires accurate and reliable algorithms for ECG analysis.
This paper deals with the development of a new algorithm for electrocardiogram (ECG) analysis for automatic diagnostic purposes. The frequency characteristic of each segment of the ECG signal is computed via a fast Fourier transform. The phase characteristic of the segments is used to identify the cardiac abnormalities. The accuracy, reliability, and consistency of the algorithm have been verified by carrying out a classification of various normal and abnormal ECG waveforms. This work is a useful step towards the goal of automatic and computerized ECG interpretation and diagnosis.
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JAFAR W. ABDUL-SADA (1988) studied Cardiac abnormalities. Algorithm for automatic ECG analysis using fast Fourier transform was evaluated on Accuracy, reliability, and consistency in classifying normal and abnormal ECG waveforms. A new fast Fourier transform-based algorithm was developed and verified to accurately classify normal and abnormal ECG waveforms for automatic computerized interpretation.
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