Advanced methods and tools for ECG data analysis / Gari D. Clifford, Francisco Azuaje, Patrick E. McSharry (editors).

Includes bibliographical references and index.

The Physiological Basis of the Electrocardiogram / Andrew T. Reisner, Gari D. Clifford, and Roger G. Mark -- ECG Acquisition, Storage, Transmission, and Representation / Gari D. Clifford and Matt B. Oefinger -- ECG Statistics, Noise, Artifacts, and Missing Data / Gari D. Clifford -- Models for ECG and RR Interval Processes / Patrick E. McSharry and Gari D. Clifford -- Linear Filtering Methods / Gari D. Clifford -- Nonlinear Filtering Techniques / Patrick E. McSharry and Gari D. Clifford -- The Pathophysiology Guided Assessment of T-Wave Alternans / Sanjiv M. Narayan -- ECG-Derived Respiratory Frequency Estimation / Raquel Bailon, Leif Sornmo, and Pablo Laguna -- Introduction to Feature Extraction / Franc Jager -- ST Analysis / Franc Jager -- Probabilistic Approaches to ECG Segmentation and Feature Extraction / Nicholas P. Hughes -- Supervised Learning Methods for ECG Classification/Neural Networks and SVM Approaches / Stanislaw Osowski, Linh Tran Hoai, and Tomasz Markiewicz -- An Introduction to Unsupervised Learning for ECG Classification / Haiying Wang and Francisco Azuaje.

Print version record.

Here's a cutting-edge, practical book that offers you a thorough understanding of state-of-the-art techniques for electrocardiogram (ECG) data analysis. Placing emphasis on the selection, modeling, classification, and interpretation of data based on advanced signal processing and artificial intelligence techniques, the book helps you design, implement, and evaluate software systems used for the analysis of ECG and related data. Publisher abstract.

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