Recognition of high-resolution ECGs by time-frequency representation

Three time-frequency (T-F) methods are evaluated for recognition of late potentials. These methods are: short-time Fourier transform (STFT), autoregressive modeling, and Wigner transform. For each method, the procedures include T-F processing, feature selection, and classification. In feature selection and classification, the authors applied both statistical pattern recognition methods like Bayesian and nearest neighbor and also artificial neural network (ANN) models. A combination of both T-F and time-domain features achieved better performance. The authors also analyzed critical issues influencing the performance of T-F methods, namely, low signal-to-noise ratio, accuracy of model estimation, and validity of assumption in using these methods