Wavelet transform for small dimension neural network pattern classification of subtly different ECGs

Adaptive wavelets for signal classification and compression

“…Here, we are using the optimum adaptive wavelet parameters which represent the signal features of ECG waves as an input to a classifier to achieve the goal of classification of ECG waves. This approach is similar to [25]. However, here, we are using the concept of adaptive sampling to obtain the optimum adaptive wavelet parameters and the VQ-based classifier that is described in Section 2.3.2 instead of the neural network-based classifier.…”

“…Therefore, it is important to detect these waves and classify them. The wavelet-based ECG waves' classifiers are reported in [25,26]. In [25], the authors have used the wavelet-based signal features in conjunction with a neural network classifier to classify PVC which is indicated by the broadening of the QRS wave, and ST-segment depression.…”