Assessing Complexity in Physiological Systems through Biomedical Signals Analysis

Assessing Complexity in Physiological Systems through Biomedical Signals Analysis PDF Author: Paolo Castiglioni
Publisher: MDPI
ISBN: 3039433687
Category : Mathematics
Languages : en
Pages : 296

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Book Description
Complexity is a ubiquitous phenomenon in physiology that allows living systems to adapt to external perturbations. Fractal structures, self-organization, nonlinearity, interactions at different scales, and interconnections among systems through anatomical and functional networks, may originate complexity. Biomedical signals from physiological systems may carry information about the system complexity useful to identify physiological states, monitor health, and predict pathological events. Therefore, complexity analysis of biomedical signals is a rapidly evolving field aimed at extracting information on the physiological systems. This book consists of 16 contributions from authors with a strong scientific background in biomedical signals analysis. It includes reviews on the state-of-the-art of complexity studies in specific medical applications, new methods to improve complexity quantifiers, and novel complexity analyses in physiological or clinical scenarios. It presents a wide spectrum of methods investigating the entropic properties, multifractal structure, self-organized criticality, and information dynamics of biomedical signals touching upon three physiological areas: the cardiovascular system, the central nervous system, the heart-brain interactions. The book is aimed at experienced researchers in signal analysis and presents the latest trends in the complexity methods in physiology and medicine with the hope of inspiring future works advancing this fascinating area of research.

Assessing Complexity in Physiological Systems through Biomedical Signals Analysis

Assessing Complexity in Physiological Systems through Biomedical Signals Analysis PDF Author: Paolo Castiglioni
Publisher: MDPI
ISBN: 3039433687
Category : Mathematics
Languages : en
Pages : 296

Get Book Here

Book Description
Complexity is a ubiquitous phenomenon in physiology that allows living systems to adapt to external perturbations. Fractal structures, self-organization, nonlinearity, interactions at different scales, and interconnections among systems through anatomical and functional networks, may originate complexity. Biomedical signals from physiological systems may carry information about the system complexity useful to identify physiological states, monitor health, and predict pathological events. Therefore, complexity analysis of biomedical signals is a rapidly evolving field aimed at extracting information on the physiological systems. This book consists of 16 contributions from authors with a strong scientific background in biomedical signals analysis. It includes reviews on the state-of-the-art of complexity studies in specific medical applications, new methods to improve complexity quantifiers, and novel complexity analyses in physiological or clinical scenarios. It presents a wide spectrum of methods investigating the entropic properties, multifractal structure, self-organized criticality, and information dynamics of biomedical signals touching upon three physiological areas: the cardiovascular system, the central nervous system, the heart-brain interactions. The book is aimed at experienced researchers in signal analysis and presents the latest trends in the complexity methods in physiology and medicine with the hope of inspiring future works advancing this fascinating area of research.

Assessing Complexity in Physiological Systems Through Biomedical Signals Analysis

Assessing Complexity in Physiological Systems Through Biomedical Signals Analysis PDF Author: Paolo Castiglioni
Publisher:
ISBN: 9783039433698
Category :
Languages : en
Pages : 296

Get Book Here

Book Description
Complexity is a ubiquitous phenomenon in physiology that allows living systems to adapt to external perturbations. Fractal structures, self-organization, nonlinearity, interactions at different scales, and interconnections among systems through anatomical and functional networks, may originate complexity. Biomedical signals from physiological systems may carry information about the system complexity useful to identify physiological states, monitor health, and predict pathological events. Therefore, complexity analysis of biomedical signals is a rapidly evolving field aimed at extracting information on the physiological systems. This book consists of 16 contributions from authors with a strong scientific background in biomedical signals analysis. It includes reviews on the state-of-the-art of complexity studies in specific medical applications, new methods to improve complexity quantifiers, and novel complexity analyses in physiological or clinical scenarios. It presents a wide spectrum of methods investigating the entropic properties, multifractal structure, self-organized criticality, and information dynamics of biomedical signals touching upon three physiological areas: the cardiovascular system, the central nervous system, the heart-brain interactions. The book is aimed at experienced researchers in signal analysis and presents the latest trends in the complexity methods in physiology and medicine with the hope of inspiring future works advancing this fascinating area of research.

Fractal and Multifractal Facets in the Structure and Dynamics of Physiological Systems and Applications to Homeostatic Control, Disease Diagnosis and Integrated Cyber-Physical Platforms

Fractal and Multifractal Facets in the Structure and Dynamics of Physiological Systems and Applications to Homeostatic Control, Disease Diagnosis and Integrated Cyber-Physical Platforms PDF Author: Paul Bogdan
Publisher: Frontiers Media SA
ISBN: 2889635317
Category :
Languages : en
Pages : 180

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Book Description
Widespread chronic diseases (e.g., heart diseases, diabetes and its complications, stroke, cancer, brain diseases) constitute a significant cause of rising healthcare costs and pose a significant burden on quality-of-life for many individuals. Despite the increased need for smart healthcare sensing systems that monitor / measure patients’ body balance, there is no coherent theory that facilitates the modeling of human physiological processes and the design and optimization of future healthcare cyber-physical systems (HCPS). The HCPS are expected to mine the patient’s physiological state based on available continuous sensing, quantify risk indices corresponding to the onset of abnormality, signal the need for critical medical intervention in real-time by communicating patient’s medical information via a network from individual to hospital, and most importantly control (actuate) vital health signals (e.g., cardiac pacing, insulin level, blood pressure) within personalized homeostasis. To prevent health complications, maintain good health and/or avoid fatal conditions calls for a cross-disciplinary approach to HCPS design where recent statistical-physics inspired discoveries done by collaborations between physicists and physicians are shared and enriched by applied mathematicians, control theorists and bioengineers. This critical and urgent multi-disciplinary approach has to unify the current state of knowledge and address the following fundamental challenges: One fundamental challenge is represented by the need to mine and understand the complexity of the structure and dynamics of the physiological systems in healthy homeostasis and associated with a disease (such as diabetes). Along the same lines, we need rigorous mathematical techniques for identifying the interactions between integrated physiologic systems and understanding their role within the overall networking architecture of healthy dynamics. Another fundamental challenge calls for a deeper understanding of stochastic feedback and variability in biological systems and physiological processes, in particular, and for deciphering their implications not only on how to mathematically characterize homeostasis, but also on defining new control strategies that are accounting for intra- and inter-patient specificity – a truly mathematical approach to personalized medicine. Numerous recent studies have demonstrated that heart rate variability, blood glucose, neural signals and other interdependent physiological processes demonstrate fractal and non-stationary characteristics. Exploiting statistical physics concepts, numerous recent research studies demonstrated that healthy human physiological processes exhibit complex critical phenomena with deep implications for how homeostasis should be defined and how control strategies should be developed when prolonged abnormal deviations are observed. In addition, several efforts have tried to connect these fractal characteristics with new optimal control strategies that implemented in medical devices such as pacemakers and artificial pancreas could improve the efficiency of medical therapies and the quality-of-life of patients but neglecting the overall networking architecture of human physiology. Consequently, rigorously analyzing the complexity and dynamics of physiological processes (e.g., blood glucose and its associated implications and interdependencies with other physiological processes) represents a fundamental step towards providing a quantifiable (mathematical) definition of homeostasis in the context of critical phenomena, understanding the onset of chronic diseases, predicting deviations from healthy homeostasis and developing new more efficient medical therapies that carefully account for the physiological complexity, intra- and inter-patient variability, rather than ignoring it. This Research Topic aims to open a synergetic and timely effort between physicians, physicists, applied mathematicians, signal processing, bioengineering and biomedical experts to organize the state of knowledge in mining the complexity of physiological systems and their implications for constructing more accurate mathematical models and designing QoL-aware control strategies implemented in the new generation of HCPS devices. By bringing together multi-disciplinary researchers seeking to understand the many aspects of human physiology and its complexity, we aim at enabling a paradigm shift in designing future medical devices that translates mathematical characteristics in predictable mathematical models quantifying not only the degree of homeostasis, but also providing fundamentally new control strategies within the personalized medicine era.

Evaluation of Systems’ Irregularity and Complexity: Sample Entropy, Its Derivatives, and Their Applications across Scales and Disciplines

Evaluation of Systems’ Irregularity and Complexity: Sample Entropy, Its Derivatives, and Their Applications across Scales and Disciplines PDF Author: Anne Humeau-Heurtier
Publisher: MDPI
ISBN: 3038973327
Category : Technology & Engineering
Languages : en
Pages : 265

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Book Description
This book is a printed edition of the Special Issue "Evaluation of Systems’ Irregularity and Complexity: Sample Entropy, Its Derivatives, and Their Applications across Scales and Disciplines" that was published in Entropy

Telemedicine and Electronic Medicine

Telemedicine and Electronic Medicine PDF Author: Halit Eren
Publisher: CRC Press
ISBN: 1351231472
Category : Business & Economics
Languages : en
Pages : 742

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Book Description
The E-Medicine, E-Health, M-Health, Telemedicine, and Telehealth Handbook provides extensive coverage of modern telecommunication in the medical industry, from sensors on and within the body to electronic medical records and beyond. Telemedicine and Electronic Medicine is the first volume of this handbook. Featuring chapters written by leading experts and researchers in their respective fields, this volume: Describes the integration of—and interactions between—modern eMedicine, telemedicine, eHealth, and telehealth practices Explains how medical information flows through wireless technologies and networks, emphasizing fast-deploying wireless body area networks Presents the latest developments in sensors, devices, and implantables, from medical sensors for mobile communication devices to drug-delivery systems Illustrates practical telemedicine applications in telecardiology, teleradiology, teledermatology, teleaudiology, teleoncology, acute care telemedicine, and more The E-Medicine, E-Health, M-Health, Telemedicine, and Telehealth Handbook bridges the gap between scientists, engineers, and medical professionals by creating synergy in the related fields of biomedical engineering, information and communication technology, business, and healthcare.

Signals and Systems Analysis In Biomedical Engineering

Signals and Systems Analysis In Biomedical Engineering PDF Author: Robert B. Northrop
Publisher: CRC Press
ISBN: 1439812535
Category : Medical
Languages : en
Pages : 656

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Book Description
The first edition of this text, based on the author's 30 years of teaching and research on neurosensory systems, helped biomedical engineering students and professionals strengthen their skills in the common network of applied mathematics that ties together the diverse disciplines that comprise this field. Updated and revised to include new materia

Nonlinear Analysis in Neuroscience and Behavioral Research

Nonlinear Analysis in Neuroscience and Behavioral Research PDF Author: Tobias A. Mattei
Publisher: Frontiers Media SA
ISBN: 2889199967
Category : Neurosciences. Biological psychiatry. Neuropsychiatry
Languages : en
Pages : 273

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Book Description
Although nonlinear dynamics have been mastered by physicists and mathematicians for a long time (as most physical systems are inherently nonlinear in nature), the recent successful application of nonlinear methods to modeling and predicting several evolutionary, ecological, physiological, and biochemical processes has generated great interest and enthusiasm among researchers in computational neuroscience and cognitive psychology. Additionally, in the last years it has been demonstrated that nonlinear analysis can be successfully used to model not only basic cellular and molecular data but also complex cognitive processes and behavioral interactions. The theoretical features of nonlinear systems (such unstable periodic orbits, period-doubling bifurcations and phase space dynamics) have already been successfully applied by several research groups to analyze the behavior of a variety of neuronal and cognitive processes. Additionally the concept of strange attractors has lead to a new understanding of information processing which considers higher cognitive functions (such as language, attention, memory and decision making) as complex systems emerging from the dynamic interaction between parallel streams of information flowing between highly interconnected neuronal clusters organized in a widely distributed circuit and modulated by key central nodes. Furthermore, the paradigm of self-organization derived from the nonlinear dynamics theory has offered an interesting account of the phenomenon of emergence of new complex cognitive structures from random and non-deterministic patterns, similarly to what has been previously observed in nonlinear studies of fluid dynamics. Finally, the challenges of coupling massive amount of data related to brain function generated from new research fields in experimental neuroscience (such as magnetoencephalography, optogenetics and single-cell intra-operative recordings of neuronal activity) have generated the necessity of new research strategies which incorporate complex pattern analysis as an important feature of their algorithms. Up to now nonlinear dynamics has already been successfully employed to model both basic single and multiple neurons activity (such as single-cell firing patterns, neural networks synchronization, autonomic activity, electroencephalographic measurements, and noise modulation in the cerebellum), as well as higher cognitive functions and complex psychiatric disorders. Similarly, previous experimental studies have suggested that several cognitive functions can be successfully modeled with basis on the transient activity of large-scale brain networks in the presence of noise. Such studies have demonstrated that it is possible to represent typical decision-making paradigms of neuroeconomics by dynamic models governed by ordinary differential equations with a finite number of possibilities at the decision points and basic heuristic rules which incorporate variable degrees of uncertainty. This e-book has include frontline research in computational neuroscience and cognitive psychology involving applications of nonlinear analysis, especially regarding the representation and modeling of complex neural and cognitive systems. Several experts teams around the world have provided frontline theoretical and experimental contributions (as well as reviews, perspectives and commentaries) in the fields of nonlinear modeling of cognitive systems, chaotic dynamics in computational neuroscience, fractal analysis of biological brain data, nonlinear dynamics in neural networks research, nonlinear and fuzzy logics in complex neural systems, nonlinear analysis of psychiatric disorders and dynamic modeling of sensorimotor coordination. Rather than a comprehensive compilation of the possible topics in neuroscience and cognitive research to which non-linear may be used, this e-book intends to provide some illustrative examples of the broad range of

Advanced Instrument Engineering: Measurement, Calibration, and Design

Advanced Instrument Engineering: Measurement, Calibration, and Design PDF Author: Lay-Ekuakille, Aimé
Publisher: IGI Global
ISBN: 1466641665
Category : Technology & Engineering
Languages : en
Pages : 358

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Book Description
Measurement technologies and instrumentation have a multidisciplinary impact in the field of applied sciences. These engineering technologies are necessary in processing information required for renewable energy, biotechnology, power quality, and nanotechnology. Advanced Instrument Engineering: Measurement, Calibration, and Design presents theoretical and practical aspects on the activities concerning measurement technologies and instrumentation. This wide range of new ideas in the field of measurements and instrumentation is useful to researchers, scientists, practitioners, and technicians for their area of expertise.

Biomechanical Spectrum of Human Sport Performance

Biomechanical Spectrum of Human Sport Performance PDF Author: Redha Taiar
Publisher: MDPI
ISBN: 3039363964
Category : Science
Languages : en
Pages : 356

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Book Description
Writing or managing a scientific book, as it is known today, depends on a series of major activities, such as regrouping researchers, reviewing chapters, informing and exchanging with contributors, and at the very least, motivating them to achieve the objective of publication. The idea of this book arose from many years of work in biomechanics, health disease, and rehabilitation. Through exchanges with authors from several countries, we learned much from each other, and we decided with the publisher to transfer this knowledge to readers interested in the current understanding of the impact of biomechanics in the analysis of movement and its optimization. The main objective is to provide some interesting articles that show the scope of biomechanical analysis and technologies in human behavior tasks. Engineers, researchers, and students from biomedical engineering and health sciences, as well as industrial professionals, can benefit from this compendium of knowledge about biomechanics applied to the human body.

Bioengineering and Biomedical Signal and Image Processing

Bioengineering and Biomedical Signal and Image Processing PDF Author: Ignacio Rojas
Publisher: Springer Nature
ISBN: 3030881636
Category : Computers
Languages : en
Pages : 521

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Book Description
This book constitutes the refereed proceedings of the First International Conference on Bioengineering and Biomedical Signal and Image Processing, BIOMESIP 2021, held in Meloneras, Gran Canaria, Spain, in July 2021. The 41 full and 5 short papers were carefully reviewed and selected from 121 submissions. The papers are grouped in topical issues on biomedical applications in molecular, structural, and functional imaging; biomedical computing; biomedical signal measurement, acquisition and processing; computerized medical imaging and graphics; disease control and diagnosis; neuroimaging; pattern recognition and machine learning for biosignal data; personalized medicine; and COVID-19.