Classifying biosignals with wavelet networks

This article reviews pattern recognition as it applies to medical diagnostics and discusses the concept of wavelet networks as a means of biosignal classification. An example is presented in which this approach was used for classifying preprocessed ECG signals to identify patients who were at high-risk of developing ventricular tachycardia (VT). The advantages of this procedure include minimized user interaction, optimally adapted features as network inputs, and a set of controlling parameters that provides an interesting description of the decision in terms of physically interpretable parameters.