Phonocardiography Signal Processing

The auscultation method is an important diagnostic indicator for hemodynamic anomalies. Heart sound classification and analysis play an important role in the auscultative diagnosis. The term phonocardiography refers to the tracing technique of heart sounds and the recording of cardiac acoustics vibration by means of a microphone-transducer. Therefore, understanding the nature and source of this signal is important to give us a tendency for developing a competent tool for further analysis and processing, in order to enhance and optimize cardiac clinical diagnostic approach. This book gives the reader an inclusive view of the main aspects in phonocardiography signal processing. Table of Contents: Introduction to Phonocardiography Signal Processing / Phonocardiography Acoustics Measurement / PCG Signal Processing Framework / Phonocardiography Wavelets Analysis / Phonocardiography Spectral Analysis / PCG Pattern Classification / Special Application of Phonocardiography / Phonocardiography Acoustic Imaging and Mapping

The major challenge in phonocardiography and heart sound analysis is the involvement of environments with adverse effects such as noise, distortion and multiple sources. Methods existing in literature which address the above said problem have their own limitations and lacunae.The objective of this research work is to investigate and develop noise estimation, noise reduction, segmentation and classification algorithms for Phonocardiograms, so as to improve the performance over the existing heart sound processing methods in literature.

The book will help assist a reader in the development of techniques for analysis of biomedical signals and computer aided diagnoses with a pedagogical examination of basic and advanced topics accompanied by over 350 figures and illustrations. Wide range of filtering techniques presented to address various applications 800 mathematical expressions and equations Practical questions, problems and laboratory exercises Includes fractals and chaos theory with biomedical applications

This book constitutes the refereed proceedings of the 6th International Conference on Computer, Communication, and Signal Processing, ICCSP 2022, held in Chennai, India, in February 2022.* The 21 full and 2 short papers presented in this volume were carefully reviewed and selected from 111 submissions. The papers are categorized into topical sub-headings: artificial intelligence and machine learning; Cyber security; and internet of things. *The conference was held as a virtual event due to the COVID-19 pandemic.

This book presents the select proceedings of the International Conference on Automation, Signal Processing, Instrumentation and Control (i-CASIC) 2020. The book mainly focuses on emerging technologies in electrical systems, IoT-based instrumentation, advanced industrial automation, and advanced image and signal processing. It also includes studies on the analysis, design and implementation of instrumentation systems, and high-accuracy and energy-efficient controllers. The contents of this book will be useful for beginners, researchers as well as professionals interested in instrumentation and control, and other allied fields.

This is the first volume in a trilogy on modern Signal Processing. The three books provide a concise exposition of signal processing topics, and a guide to support individual practical exploration based on MATLAB programs. This book includes MATLAB codes to illustrate each of the main steps of the theory, offering a self-contained guide suitable for independent study. The code is embedded in the text, helping readers to put into practice the ideas and methods discussed. The book is divided into three parts, the first of which introduces readers to periodic and non-periodic signals. The second part is devoted to filtering, which is an important and commonly used application. The third part addresses more advanced topics, including the analysis of real-world non-stationary signals and data, e.g. structural fatigue, earthquakes, electro-encephalograms, birdsong, etc. The book’s last chapter focuses on modulation, an example of the intentional use of non-stationary signals.

Advanced techniques in image processing have led to many innovations supporting the medical field, especially in the area of disease diagnosis. Biomedical imaging is an essential part of early disease detection and often considered a first step in the proper management of medical pathological conditions. Classification and Clustering in Biomedical Signal Processing focuses on existing and proposed methods for medical imaging, signal processing, and analysis for the purposes of diagnosing and monitoring patient conditions. Featuring the most recent empirical research findings in the areas of signal processing for biomedical applications with an emphasis on classification and clustering techniques, this essential publication is designed for use by medical professionals, IT developers, and advanced-level graduate students.

A complete guide to using multimodal imaging in cardiac practice 4 STAR DOODY'S REVIEW! "In addition to compiling the various imaging modalities used for clinical diagnosis in cardiovascular disease, the book also summarizes the present and future applications of combined imaging modalities for better understanding the underlying pathophysiologic basis of cardiovascular diseases....This book is unique in the way it comprehensively reviews both the current and future applications of multiple imaging modalities."--Doody's Review Service Multimodal Cardiovascular Imaging: Principles and Clinical Applications offers a unique “matrix” approach to help you choose the most appropriate combination of imaging modalities for the management of patients with cardiovascular disease. The book discusses the various options available, how they work, the benefits and drawbacks of each, and what modalities will best work in conjunction with each other for a specific condition. Featuring contributions from more than 60 international authors and enriched by 225 half-tone modality images and 130 full-color illustrations, Multimodal Cardiovascular Imaging: Principles and Clinical Applications is divided into three sections: Section 1 contains chapters that focus on the use of ten specific clinically available diagnostic modalities and their broad application to clinical cardiology. Modalities discussed include: Echocardiography Phonocardiography Myocardial Perfusion SPECT and PET Coronary Angiography Cardiac CT Section 2 includes six chapters that present “visions of the future” for combining multiple diagnostic modalities. They form the foundation for understanding the pathophysiologic basis of clinical cardiovascular conditions using prototypes, simulations, models, and tutorials. Section 3 considers several cardiovascular conditions and how multimodal imaging can provide diagnostic and therapeutic decision support to optimize the clinical care for each of them. Some chapters in this section also include case reports of how clinicians/scientists are using multimodal imaging modalities to improve their clinical therapeutic decision support. Conditions include: Congenital Heart Disease Ischemic Heart Disease Acute Myocardial Infarction Aortic Disease Atrial Fibrillation