Advances in Cardiac Signal Processing

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Acharya, U. Rajendra (Επιμελητής έκδοσης), Suri, Jasjit S. (Επιμελητής έκδοσης), Spaan, Jos A. E. (Επιμελητής έκδοσης), Krishnan, Shankar M. (Επιμελητής έκδοσης)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg, 2007.
• Θέματα: Engineering.; Cardiology.; Statistical physics.; Dynamical systems.; Computational intelligence.; Biomedical engineering.; Signal, Image and Speech Processing.; Statistical Physics, Dynamical Systems and Complexity.; Computational Intelligence.; Biomedical Engineering.

 This book deals with the acquisition and extraction of the various morphological features of the electrocardiogram signals. In the first chapters the book first presents data fusion and different data mining techniques that have been used for the cardiac state diagnosis. The second part deals with heart rate variability (HRV), a non-invasive measurement of cardiovascular autonomic regulation. Next, visualization of ECG data is discussed, an important part of the display in life threatening state. Here, the handling of data is discussed which were acquired during several hours. In the following chapters the book discusses aortic pressure measurement which is of significant clinical importance. It presents non-invasive methods for analysis of the aortic pressure waveform, indicating how it can be employed to determine cardiac contractility, arterial compliance, and peripheral resistance. In addition, the book demonstrates methods to extract diagnostic parameters for assessing cardiac function. Further the measurement strategies for contractile effort of the left ventricle are presented. Finally, the book concludes about the future of cardiac signal processing leading to next generation research topics which directly impacts the cardiac health care. The editors thank Biocom Technologies for the provided scientific material and help in writing the book. 

 The Electrocardiogram -- Analysis of Electrocardiograms -- Prediction of Cardiac Signals Using Linear and Nonlinear Techniques -- Visualization of Cardiac Health Using Electrocardiograms -- Heart Rate Variability -- Data Fusion of Multimodal Cardiovascular Signals -- Classification of Cardiac Patient States Using Artificial Neural Networks -- The Application of Autoregressive Modeling in Cardiac Arrhythmia Classification -- Classification of Cardiac Abnormalities Using Heart Rate Signals: A Comparative Study -- Storage and Transmission of Cardiac Data with Medical Images -- Assessment of Cardiac Function in Filling amp; Systolic Ejection Phases: A Mathematical and Clinical Evaluation -- Arterial Wave Propagation and Reflection at a Bifurcation Site -- ECG Signal Conditioning by Morphological Filters -- Multivariate Analysis for Cardiovascular and Respiratory Signals -- Phase Space Analysis for Cardiovascular Signals -- Linear, Non-Linear and Wavelet Analysis of Cardiac Health Using Heart Rate Signals -- Soft Tissue Biomechanics of the Left Ventricular Myocardium -- Wavelets and its Application in Cardiology -- 1/f Fluctuation of Heart Rate in Postoperative and Brain-Dead Patients -- Stress During Speech Therapy.