Assessing Complexity in Physiological Systems through Biomedical Signals Analysis

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 comple...

Full description

Saved in:
Bibliographic Details
HerausgeberIn:
Sonstige:
Year of Publication:2021
Language:English
Physical Description:1 electronic resource (296 p.)
Tags: Add Tag
No Tags, Be the first to tag this record!
LEADER 05552nam-a2201297z--4500
001 993546594004498
005 20240312174103.0
006 m o d
007 cr|mn|---annan
008 202105s2021 xx |||||o ||| 0|eng d
035 |a (CKB)5400000000045385 
035 |a (oapen)https://directory.doabooks.org/handle/20.500.12854/68427 
035 |a (EXLCZ)995400000000045385 
041 0 |a eng 
100 1 |a Castiglioni, Paolo  |4 edt 
245 1 0 |a Assessing Complexity in Physiological Systems through Biomedical Signals Analysis 
260 |a Basel, Switzerland  |b MDPI - Multidisciplinary Digital Publishing Institute  |c 2021 
300 |a 1 electronic resource (296 p.) 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
506 |a Open access  |f Unrestricted online access  |2 star 
520 |a 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. 
546 |a English 
650 7 |a Research & information: general  |2 bicssc 
650 7 |a Mathematics & science  |2 bicssc 
653 |a autonomic nervous function 
653 |a heart rate variability (HRV) 
653 |a baroreflex sensitivity (BRS) 
653 |a photo-plethysmo-graphy (PPG) 
653 |a digital volume pulse (DVP) 
653 |a percussion entropy index (PEI) 
653 |a heart rate variability 
653 |a posture 
653 |a entropy 
653 |a complexity 
653 |a cognitive task 
653 |a sample entropy 
653 |a brain functional networks 
653 |a dynamic functional connectivity 
653 |a static functional connectivity 
653 |a K-means clustering algorithm 
653 |a fragmentation 
653 |a aging in human population 
653 |a factor analysis 
653 |a support vector machines classification 
653 |a Sampen 
653 |a cross-entropy 
653 |a autonomic nervous system 
653 |a heart rate 
653 |a blood pressure 
653 |a hypobaric hypoxia 
653 |a rehabilitation medicine 
653 |a labor 
653 |a fetal heart rate 
653 |a data compression 
653 |a complexity analysis 
653 |a nonlinear analysis 
653 |a preterm 
653 |a Alzheimer’s disease 
653 |a brain signals 
653 |a single-channel analysis 
653 |a biomarker 
653 |a refined composite multiscale entropy 
653 |a central autonomic network 
653 |a interconnectivity 
653 |a ECG 
653 |a ectopic beat 
653 |a baroreflex 
653 |a self-organized criticality 
653 |a vasovagal syncope 
653 |a Zipf’s law 
653 |a multifractality 
653 |a multiscale complexity 
653 |a detrended fluctuation analysis 
653 |a self-similarity 
653 |a sEMG 
653 |a approximate entropy 
653 |a fuzzy entropy 
653 |a fractal dimension 
653 |a recurrence quantification analysis 
653 |a correlation dimension 
653 |a largest Lyapunov exponent 
653 |a time series analysis 
653 |a relative consistency 
653 |a event-related de/synchronization 
653 |a motor imagery 
653 |a vector quantization 
653 |a information dynamics 
653 |a partial information decomposition 
653 |a conditional transfer entropy 
653 |a network physiology 
653 |a multivariate time series analysis 
653 |a State–space models 
653 |a vector autoregressive model 
653 |a penalized regression techniques 
653 |a linear prediction 
653 |a fNIRS 
653 |a brain dynamics 
653 |a mental arithmetics 
653 |a multiscale 
653 |a cardiovascular system 
653 |a brain 
653 |a information flow 
776 |z 3-03943-368-7 
776 |z 3-03943-369-5 
700 1 |a Faes, Luca  |4 edt 
700 1 |a Valenza, Gaetano  |4 edt 
700 1 |a Castiglioni, Paolo  |4 oth 
700 1 |a Faes, Luca  |4 oth 
700 1 |a Valenza, Gaetano  |4 oth 
906 |a BOOK 
ADM |b 2024-03-13 11:01:51 Europe/Vienna  |f system  |c marc21  |a 2022-04-04 09:22:53 Europe/Vienna  |g false 
AVE |i DOAB Directory of Open Access Books  |P DOAB Directory of Open Access Books  |x https://eu02.alma.exlibrisgroup.com/view/uresolver/43ACC_OEAW/openurl?u.ignore_date_coverage=true&portfolio_pid=5338240790004498&Force_direct=true  |Z 5338240790004498  |b Available  |8 5338240790004498