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An early detection and diagnosis of atrial fibrillation sets the course for timely intervention to prevent potentially occurring comorbidities. Electrocardiogram data resulting from electrophysiological cohort modeling and simulation can be a valuable data resource for improving automated atrial fibrillation risk stratification with machine learning techniques and thus, reduces the risk of stroke in affected patients.
Photoplethysmography: Technology, Signal Analysis, and Applications is the first comprehensive volume on the theory, principles, and technology (sensors and electronics) of photoplethysmography (PPG). It provides a detailed description of the current state-of-the-art technologies/optical components enabling the extreme miniaturization of such sensors, as well as comprehensive coverage of PPG signal analysis techniques including machine learning and artificial intelligence. The book also outlines the huge range of PPG applications in healthcare, with a strong focus on the contribution of PPG in wearable sensors and PPG for cardiovascular assessment. - Presents the underlying principles and technology surrounding PPG - Includes applications for healthcare and wellbeing - Focuses on PPG in wearable sensors and devices - Presents advanced signal analysis techniques - Includes cutting-edge research, applications and future directions
Electrical activity in the myocardium coordinates the contraction of the heart, and its knowledge could lead to a better understanding, diagnosis, and treatment of cardiac diseases. This electrical activity generates an electromagnetic field that propagates outside the heart and reaches the human torso surface, where it can be easily measured. Classical electrocardiography aims to interpret the 12-lead electrocardiogram (ECG) to determine cardiac activity and support the diagnosis of cardiac pathologies such as arrhythmias, altered activations, and ischemia. More recently, a higher number of leads is used to reconstruct a more detailed quantitative description of the electrical activity in the heart by solving the so-called inverse problem of electrocardiography. This technique is known as ECG imaging. Today, clinical applications of ECG imaging are showing promising results in guiding a variety of electrophysiological interventions such as catheter ablation of atrial fibrillation and ventricular tachycardia. However, in order to promote the adoption of ECG imaging in the routine clinical practice, further research is required regarding more accurate mathematical methods, further scientific validation under different preclinical scenarios and a more extensive clinical validation
This book provides a thorough introduction to the topic of mathematical modeling of electrical activity in the heart, from molecular details of ionic channel dynamics to clinically derived patient-specific models. It discusses how cellular ionic models are formulated, introduces commonly used models and explains why there are so many different models available. The chapters cover modeling of the intracellular calcium handling that underlies cellular contraction as well as modeling molecular-level details of cardiac ion channels, and also focus on specialized topics such as cardiomyocyte energetics and signalling pathways. It is an excellent resource for experienced and specialised researchers in the field, but also biological scientists with a limited background in mathematical modelling and computational methods. Part of Biophysical Society-IOP series.
Precision Medicine and Artificial Intelligence: The Perfect Fit for Autoimmunity covers background on artificial intelligence (AI), its link to precision medicine (PM), and examples of AI in healthcare, especially autoimmunity. The book highlights future perspectives and potential directions as AI has gained significant attention during the past decade. Autoimmune diseases are complex and heterogeneous conditions, but exciting new developments and implementation tactics surrounding automated systems have enabled the generation of large datasets, making autoimmunity an ideal target for AI and precision medicine. More and more diagnostic products utilize AI, which is also starting to be supported by regulatory agencies such as the Food and Drug Administration (FDA). Knowledge generation by leveraging large datasets including demographic, environmental, clinical and biomarker data has the potential to not only impact the diagnosis of patients, but also disease prediction, prognosis and treatment options. - Allows the readers to gain an overview on precision medicine for autoimmune diseases leveraging AI solutions - Provides background, milestone and examples of precision medicine - Outlines the paradigm shift towards precision medicine driven by value-based systems - Discusses future applications of precision medicine research using AI - Other aspects covered in the book include regulatory insights, data analytics and visualization, types of biomarkers as well as the role of the patient in precision medicine
The goal of ICITCS s 6th International Conference is to bring researchers from academia and practitioners from on IT Convergence and Security ICITCS 2016 is the next event in the series of highly successful International Conferences on Information Science and Applications, previously held in Kuala Lumpur, Malaysia (2015), Beijing, China (2014), Macau (2013), Pyeong Chang, Korea (2012), and Suwon, Korea (2011) 3rd, 4th and 5th Conferences were technically sponsored by IEEE Computer Society and proceedings were published in IEEE Xplore 1st and 2nd Conferences were technically sponsored by LNEE (Springer) and proceedings were published in LNEE Series IEEE Xplore and LNEE Series were indexed by EI, ISI, and Scopus ICITCS seeks contributions presenting novel research results in all aspects of IT Convergence and Security Submitted papers will be peer reviewed Furthermore, the selected papers will be published in the special issues of prestigious international journals after furt
The Poincaré plot (named after Henri Poincaré) is a popular two-dimensional visualization tool for dynamic systems due to its intuitive display of the dynamic properties of a system from a time series. This book presents the basis of Poincaré plot and focus especially on traditional and new methods for analysing the geometry, temporal and spatial dynamics disclosed by the Poincaré plot to evaluate heart rate variability (HRV). Mathematical descriptors of Poincaré plot have been developed to quantify the autonomic nervous system activity (sympathetic and parasympathetic modulation of heart rate). Poincaré plot analysis has also been used in various clinical diagnostic settings like diabetes, chronic heart failure, chronic renal failure and sleep apnea syndrome. The primary aims of quantification of the Poincaré plots are to discriminate healthy physiological systems from pathological conditions and to classify the stage of a disease. The HRV analysis by Poincaré plot has opened up ample opportunities for important clinical and research applications. Therefore, the present book can be used either for self-study, as a supplement to courses in linear and nonlinear systems, or as a modern monograph by researchers in this field of HRV analysis.
This book provides a comprehensive guide to the state-of-the-art in cardiovascular computing and highlights novel directions and challenges in this constantly evolving multidisciplinary field. The topics covered span a wide range of methods and clinical applications of cardiovascular computing, including advanced technologies for the acquisition and analysis of signals and images, cardiovascular informatics, and mathematical and computational modeling.
These papers are concerned with new advances and novel solutions in the areas of biofluids, image-guided surgery, tissue engineering and cardovascular mechanics, implant analysis, soft tissue mechanics, bone remodeling and motion analysis. The contents also feature a special section on dental materials, dental adhesives and orthodontic mechanics. This edition contains many examples, tables and figures, and together with the many references, provides the reader with invaluable information on the latest theoretical developments and applications.
The detection and recognition of objects in images is a key research topic in the computer vision community. Within this area, face recognition and interpretation has attracted increasing attention owing to the possibility of unveiling human perception mechanisms, and for the development of practical biometric systems. This book and the accompanying website, focus on template matching, a subset of object recognition techniques of wide applicability, which has proved to be particularly effective for face recognition applications. Using examples from face processing tasks throughout the book to illustrate more general object recognition approaches, Roberto Brunelli: examines the basics of digital image formation, highlighting points critical to the task of template matching; presents basic and advanced template matching techniques, targeting grey-level images, shapes and point sets; discusses recent pattern classification paradigms from a template matching perspective; illustrates the development of a real face recognition system; explores the use of advanced computer graphics techniques in the development of computer vision algorithms. Template Matching Techniques in Computer Vision is primarily aimed at practitioners working on the development of systems for effective object recognition such as biometrics, robot navigation, multimedia retrieval and landmark detection. It is also of interest to graduate students undertaking studies in these areas.