05700nam 2201345z- 450 991055760180332120210501(CKB)5400000000045385(oapen)https://directory.doabooks.org/handle/20.500.12854/68427(oapen)doab68427(EXLCZ)99540000000004538520202105d2021 |y 0engurmn|---annantxtrdacontentcrdamediacrrdacarrierAssessing Complexity in Physiological Systems through Biomedical Signals AnalysisBasel, SwitzerlandMDPI - Multidisciplinary Digital Publishing Institute20211 online resource (296 p.)3-03943-368-7 3-03943-369-5 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.Mathematics & sciencebicsscResearch & information: generalbicsscaging in human populationAlzheimer's diseaseapproximate entropyautonomic nervous functionautonomic nervous systembaroreflexbaroreflex sensitivity (BRS)biomarkerblood pressurebrainbrain dynamicsbrain functional networksbrain signalscardiovascular systemcentral autonomic networkcognitive taskcomplexitycomplexity analysisconditional transfer entropycorrelation dimensioncross-entropydata compressiondetrended fluctuation analysisdigital volume pulse (DVP)dynamic functional connectivityECGectopic beatentropyevent-related de/synchronizationfactor analysisfetal heart ratefNIRSfractal dimensionfragmentationfuzzy entropyheart rateheart rate variabilityheart rate variability (HRV)hypobaric hypoxiainformation dynamicsinformation flowinterconnectivityK-means clustering algorithmlaborlargest Lyapunov exponentlinear predictionmental arithmeticsmotor imagerymultifractalitymultiscalemultiscale complexitymultivariate time series analysisnetwork physiologynonlinear analysispartial information decompositionpenalized regression techniquespercussion entropy index (PEI)photo-plethysmo-graphy (PPG)posturepretermrecurrence quantification analysisrefined composite multiscale entropyrehabilitation medicinerelative consistencySampensample entropyself-organized criticalityself-similaritysEMGsingle-channel analysisState-space modelsstatic functional connectivitysupport vector machines classificationtime series analysisvasovagal syncopevector autoregressive modelvector quantizationZipf's lawMathematics & scienceResearch & information: generalCastiglioni Paoloedt1319355Faes LucaedtValenza GaetanoedtCastiglioni PaoloothFaes LucaothValenza GaetanoothBOOK9910557601803321Assessing Complexity in Physiological Systems through Biomedical Signals Analysis3033816UNINA