Assessing Complexity in Physiological Systems through Biomedical Signals Analysis

• Autore: Castiglioni Paolo
• Pubblicazione: Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021
• Descrizione fisica: 1 online resource (296 p.)
• Soggetto topico: Mathematics & science; Research & information: general
• Soggetto non controllato: aging in human population; Alzheimer's disease; approximate entropy; autonomic nervous function; autonomic nervous system; baroreflex; baroreflex sensitivity (BRS); biomarker; blood pressure; brain; brain dynamics; brain functional networks; brain signals; cardiovascular system; central autonomic network; cognitive task; complexity; complexity analysis; conditional transfer entropy; correlation dimension; cross-entropy; data compression; detrended fluctuation analysis; digital volume pulse (DVP); dynamic functional connectivity; ECG; ectopic beat; entropy; event-related de/synchronization; factor analysis; fetal heart rate; fNIRS; fractal dimension; fragmentation; fuzzy entropy; heart rate; heart rate variability; heart rate variability (HRV); hypobaric hypoxia; information dynamics; information flow; interconnectivity; K-means clustering algorithm; labor; largest Lyapunov exponent; linear prediction; mental arithmetics; motor imagery; multifractality; multiscale; multiscale complexity; multivariate time series analysis; network physiology; nonlinear analysis; partial information decomposition; penalized regression techniques; percussion entropy index (PEI); photo-plethysmo-graphy (PPG); posture; preterm; recurrence quantification analysis; refined composite multiscale entropy; rehabilitation medicine; relative consistency; Sampen; sample entropy; self-organized criticality; self-similarity; sEMG; single-channel analysis; State-space models; static functional connectivity; support vector machines classification; time series analysis; vasovagal syncope; vector autoregressive model; vector quantization; Zipf's law
• Persona (resp. second.): FaesLuca; ValenzaGaetano; CastiglioniPaolo
• Sommario/riassunto: 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.
• Titolo autorizzato: Assessing Complexity in Physiological Systems through Biomedical Signals Analysis
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910557601803321
• Lo trovi qui: Univ. Federico II