Entropy Methods for Cardiorespiratory Coupling Analysis
A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Entropy and Biology".
Deadline for manuscript submissions: 20 October 2024 | Viewed by 254
Special Issue Editors
Interests: biomedical signal analysis; biophysics; medical physics; heart rate variability; cardiorespiratory coupling; brain-cardiopulmonary coupling-stomach axis; metabolism
Interests: biomedical signal analysis; heart rate variability; cardiovascular control; cardiorespiratory coupling; multivariate time series analysis; nonlinear dynamics
Interests: portable/wearable monitoring systems; electrocardiographic (ECG) and photoplethysmographic (PPG) acquisition sensors and systems; biomedical signal processing; autonomic nervous system; heart rate variability (HRV) analysis; brain–heart interactions
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Entropy is a nonlinear measure employed to quantify the dynamical properties of biomedical signals. Various methods based on Shannon entropy have been applied to estimate the complexity or irregularity of multivariate signals over multiple scales; these have also been utilized in the analysis of cardiac and respiratory time series to examine the features of bidirectional cardiorespiratory interactions. In the last few decades, in addition to the neural control of the heart rhythm, many basic and clinical studies have revealed the properties of the neural control of breathing. However, we remain unable to recognize the whole spectrum of the variability in cardiorespiratory coupling during wakefulness, sleep, exercise or changes in the cardiovascular and respiratory system induced by pathological conditions. This Special Issue aims to disseminate the results obtained via the development of novel entropy metrics and/or the implementation of standard entropy measures under the different physiological and pathological conditions applicable in the examination of cardiorespiratory interactions.
Prof. Dr. Mirjana M. Platiša
Dr. Beatrice Cairo
Dr. Riccardo Pernice
Guest Editors
Manuscript Submission Information
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Keywords
- cardiopulmonary coupling
- exercise
- pulmonary diseases
- heart failure
- nonstationary time series
