| Review: |
This book collects together current research in ECG analysis as a guide to applying complex techniques in this field. It gives an overview of many of the most interesting and useful advanced techniques that are currently available, giving the reader the relevant background on where distortion, noise and errors can creep into an experiment or analysis. There are chapters on: The physiological basis of the electrocardiogram; ECG acquisition, storage, transmission and representation; ECG statistics, noise, artifacts, and missing data; Models for ECG and RR interval processes; Linear filtering methods, Nonlinear filtering techniques; The pathophysiology guided assessment of T-wave alternans; ECG derived respiratory frequency estimation; Introduction to feature extraction; ST analysis; Probabilistic approaches to ECG segmentation and feature extraction; Supervised learning methods for ECG classification/Neural networks and SVM approaches; and An introduction to unsupervised learning for ECG classification. |