Classification of the electrocardiogram using selected wavelet coefficients and linear discriminants
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Citation:deChazal, P., Reilly, G., McDarby, G. and Celler, B. 'Classification of the electrocardiogram using selected wavelet coefficients and linear discriminants' in Proceedings of 2000 IEEE International Conference on Acoustics, Speech and Signal Processing, Istanbul, June, 6, IEEE, 2000, pp 3590 - 3593.
Twenty-live wavelet coefficients were selected as inputs and cross-validation used to estimate the classifier performance. An overall accuracy of 72.3% was achieved using a database of 500 ECG records independently classified into seven classes. This compared well with published cardiologist classification rates. By introducing a no-classification state, the accuracy increased to 7.9% with 80% of ECG records classified. The method presented here is not specific to the ECG domain and may easily be applied to other classification problems
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