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...
Saved in:
| Format: | Online |
|---|---|
| Language: | English |
| Published: |
MDPI - Multidisciplinary Digital Publishing Institute
2026
|
| Subjects: | |
| Online Access: | ONIX_20260416T142754_9783725863662_2 |
| Tags: |
No Tags, Be the first to tag this record!
|
| _version_ | 1869514211682418688 |
|---|---|
| collection | Directory of Open Access Books |
| description | 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, nonlinear dynamics, and the coordinated activity of interdependent components operating across multiple hierarchical levels and time scales. Biomedical signals encode aspects of this complexity, supporting the identification of physiological states, long-term health monitoring, and the anticipation of pathological events. As a result, contemporary research has focused on methods capable of characterizing system complexity in time series derived from continuous electroencephalogram and electromyogram recordings, cardiovascular beat-by-beat measurements, respiratory patterns, and other physiological variables. Despite substantial progress, key methodological challenges remain, including differentiating complexity from randomness, ensuring robust estimation from short or multivariate recordings, integrating multivariate measures of predictability, entropy, and fractality, and describing the underlying stochastic processes. This Reprint is the second volume in its series, following the initial Entropy Special Issue printed in 2021. Building on the significant interest generated by that collection, this volume presents recent studies which aimed to enhance the applications of complexity-based methods in physiological and clinical contexts. |
| format | Online |
| id | doab-20.500.12854ir-175397 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2026 |
| publishDateRange | 2026 |
| publishDateSort | 2026 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-1753972026-04-16T20:41:50Z Assessing Complexity in Physiological Systems through Biomedical Signals Analysis II Castiglioni, Paolo Faes, Luca Valenza, Gaetano Faini, Andrea 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 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, nonlinear dynamics, and the coordinated activity of interdependent components operating across multiple hierarchical levels and time scales. Biomedical signals encode aspects of this complexity, supporting the identification of physiological states, long-term health monitoring, and the anticipation of pathological events. As a result, contemporary research has focused on methods capable of characterizing system complexity in time series derived from continuous electroencephalogram and electromyogram recordings, cardiovascular beat-by-beat measurements, respiratory patterns, and other physiological variables. Despite substantial progress, key methodological challenges remain, including differentiating complexity from randomness, ensuring robust estimation from short or multivariate recordings, integrating multivariate measures of predictability, entropy, and fractality, and describing the underlying stochastic processes. This Reprint is the second volume in its series, following the initial Entropy Special Issue printed in 2021. Building on the significant interest generated by that collection, this volume presents recent studies which aimed to enhance the applications of complexity-based methods in physiological and clinical contexts. 2026-04-16T20:41:41Z 2026-04-16T20:41:41Z 2026 book ONIX_20260416T142754_9783725863662_2 9783725863662 9783725863679 https://directory.doabooks.org/handle/20.500.12854/175397 eng application/octet-stream Attribution 4.0 International https://mdpi.com/books/ https://mdpi.com/books/pdfview/book/12315 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-7258-6367-9 10.3390/books978-3-7258-6367-9 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783725863662 9783725863679 218 CH open access |
| spellingShingle | 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 Assessing Complexity in Physiological Systems through Biomedical Signals Analysis II |
| title | Assessing Complexity in Physiological Systems through Biomedical Signals Analysis II |
| title_full | Assessing Complexity in Physiological Systems through Biomedical Signals Analysis II |
| title_fullStr | Assessing Complexity in Physiological Systems through Biomedical Signals Analysis II |
| title_full_unstemmed | Assessing Complexity in Physiological Systems through Biomedical Signals Analysis II |
| title_short | Assessing Complexity in Physiological Systems through Biomedical Signals Analysis II |
| title_sort | assessing complexity in physiological systems through biomedical signals analysis ii |
| topic | 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 |
| topic_facet | 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 |
| url | ONIX_20260416T142754_9783725863662_2 |