Assessing Complexity in Physiological Systems through Biomedical Signals Analysis II

Most physiological systems behave like complex, adaptive structures. In physiology and medicine, this complexity reflects the capacity of living systems to maintain homeostasis while responding to internal and external challenges, arising from features such as fractal- and self-organization, nonline...

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Bibliographic Details
Format:	Online
Language:	English
Published:	MDPI - Multidisciplinary Digital Publishing Institute 2026
Subjects:	Heart rate variability Inhibitory control Complexity index Entropy Multiscale entropy Spinal cord injury Posture Autonomic nervous system SampEn FuzzyEn DistEn Visibility Tachograms K-M slope Complex networks Average degree Average path length Baroreflex Blood pressure regulation Cardiovascular dynamics Homeostasis Fractal Self-organized criticality Soccer Zipf’s law Fractal dimension Box-counting EEG Parkinson’s disease Neurodegeneration Cardiovascular Multifractality DFA Autonomic control Heart–brain Central autonomic network Cognitive task Detrended fluctuation analysis Multifractal Multiscale analysis Cycling Tetris Multifractal cumulative function Legendre spectrum Electroencephalography (EEG) Multi-entropy fusion Brain rhythms Single-channel Emotion recognition Schizophrenia Electroencephalography Higuchi fractal dimension Neural complexity Temporal dynamics Spike train Artificial neural networks Biological neurons Intermittency Criticality Tricriticality Phase transitions Stockwell transform Stockwell entropy Common spatial pattern Parameterized PSD Aperiodic component Periodic component Specific language impairment Network physiology Functional near-infrared spectroscopy Power spectral density Information dynamics Time-resolved analysis Time-varying autoregressive modeling Recursive least-squares N A thema EDItEUR::M Medicine and Nursing
Online Access:	ONIX_20260416T142754_9783725863662_2
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Assessing Complexity in Physiological Systems through Biomedical Signals Analysis II

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