Castiglioni, Paolo <br/><br/>
Assessing Complexity in Physiological Systems through Biomedical Signals Analysis 

 - Basel, Switzerland  MDPI - Multidisciplinary Digital Publishing Institute  2021 
 - 1 electronic resource (296 p.) 
<br/><br/> Open Access 
<br/><br/> 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. 
<br/><br/><br/>Creative Commons 
<br/><br/><br/>English 
<br/><br/><label>ISBN: </label>books978-3-03943-369-8 9783039433681 9783039433698 
<br/><br/><label>Standard No.: </label>10.3390/books978-3-03943-369-8  doi 
<br/><br/><label>Subjects--Topical Terms: </label><br/>Research & information: general<br/>Mathematics & science
<br/><br/><label>Subjects--Index Terms: </label>autonomic nervous function heart rate variability (HRV) baroreflex sensitivity (BRS) photo-plethysmo-graphy (PPG) digital volume pulse (DVP) percussion entropy index (PEI) heart rate variability posture entropy complexity cognitive task sample entropy brain functional networks dynamic functional connectivity static functional connectivity K-means clustering algorithm fragmentation aging in human population factor analysis support vector machines classification Sampen cross-entropy autonomic nervous system heart rate blood pressure hypobaric hypoxia rehabilitation medicine labor fetal heart rate data compression complexity analysis nonlinear analysis preterm Alzheimer’s disease brain signals single-channel analysis biomarker refined composite multiscale entropy central autonomic network interconnectivity ECG ectopic beat baroreflex self-organized criticality vasovagal syncope Zipf’s law multifractality multiscale complexity detrended fluctuation analysis self-similarity sEMG approximate entropy fuzzy entropy fractal dimension recurrence quantification analysis correlation dimension largest Lyapunov exponent time series analysis relative consistency event-related de/synchronization motor imagery vector quantization information dynamics partial information decomposition conditional transfer entropy network physiology multivariate time series analysis State–space models vector autoregressive model penalized regression techniques linear prediction fNIRS brain dynamics mental arithmetics multiscale cardiovascular system brain information flow