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RESEARCH PRODUCT
Assessment of Cardiorespiratory Interactions during Apneic Events in Sleep via Fuzzy Kernel Measures of Information Dynamics
Gorana MijatovicIvan LazicTatjana Loncar-turukaloRiccardo PerniceLuca Faessubject
Information transfermedicine.medical_specialtyScienceQC1-999General Physics and AstronomyAstrophysics01 natural sciencesArticle010305 fluids & plasmas03 medical and health sciences0302 clinical medicinePhysical medicine and rehabilitation0103 physical sciencesrespiratory effort-related arousal (RERA)MedicineVagal toneinformation dynamicbusiness.industryPhysicsQCardiorespiratory interactionApneaCardiorespiratory fitnessCognitioncardiorespiratory interactionsapneaRisk factor (computing)QB460-466Settore ING-INF/06 - Bioingegneria Elettronica E InformaticaBreathingSleep (system call)medicine.symptominformation dynamicsentropybusiness030217 neurology & neurosurgerydescription
Apnea and other breathing-related disorders have been linked to the development of hypertension or impairments of the cardiovascular, cognitive or metabolic systems. The combined assessment of multiple physiological signals acquired during sleep is of fundamental importance for providing additional insights about breathing disorder events and the associated impairments. In this work, we apply information-theoretic measures to describe the joint dynamics of cardiorespiratory physiological processes in a large group of patients reporting repeated episodes of hypopneas, apneas (central, obstructive, mixed) and respiratory effort related arousals (RERAs). We analyze the heart period as the target process and the airflow amplitude as the driver, computing the predictive information, the information storage, the information transfer, the internal information and the cross information, using a fuzzy kernel entropy estimator. The analyses were performed comparing the information measures among segments during, immediately before and after the respiratory event and with control segments. Results highlight a general tendency to decrease of predictive information and information storage of heart period, as well as of cross information and information transfer from respiration to heart period, during the breathing disordered events. The information-theoretic measures also vary according to the breathing disorder, and significant changes of information transfer can be detected during RERAs, suggesting that the latter could represent a risk factor for developing cardiovascular diseases. These findings reflect the impact of different sleep breathing disorders on respiratory sinus arrhythmia, suggesting overall higher complexity of the cardiac dynamics and weaker cardiorespiratory interactions which may have physiological and clinical relevance.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2021-05-31 | Entropy |