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Assessing Complexity in Physiological Systems through Biomedical Signals Analysis



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Autore: Castiglioni Paolo Visualizza persona
Titolo: Assessing Complexity in Physiological Systems through Biomedical Signals Analysis Visualizza cluster
Pubblicazione: Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021
Descrizione fisica: 1 electronic resource (296 p.)
Soggetto topico: Research & information: general
Mathematics & science
Soggetto non controllato: 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
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  Visualizza cluster
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910557601803321
Lo trovi qui: Univ. Federico II
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