0000000000538178

AUTHOR

Zuzana Lazarova

showing 5 related works from this author

Towards understanding the complexity of cardiovascular oscillations: Insights from information theory.

2018

Abstract Cardiovascular complexity is a feature of healthy physiological regulation, which stems from the simultaneous activity of several cardiovascular reflexes and other non-reflex physiological mechanisms. It is manifested in the rich dynamics characterizing the spontaneous heart rate and blood pressure variability (HRV and BPV). The present study faces the challenge of disclosing the origin of short-term HRV and BPV from the statistical perspective offered by information theory. To dissect the physiological mechanisms giving rise to cardiovascular complexity in different conditions, measures of predictive information, information storage, information transfer and information modificati…

Blood pressure variabilityAdultMalemedicine.medical_specialtySupine positionAdolescent0206 medical engineeringInformation TheoryHealth InformaticsBlood Pressure02 engineering and technologyBaroreflexCardiovascular Physiological Phenomena03 medical and health sciencesElectrocardiographyYoung AdultRedundancy0302 clinical medicineHeart RateInternal medicineHeart ratemedicineHeart rate variabilityHumansVagal toneHeart rate variabilitybusiness.industryModels CardiovascularCardiorespiratory fitnessSignal Processing Computer-AssistedComplexity020601 biomedical engineeringComputer Science ApplicationsCausalityBlood pressureSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaCardiologyFemalebusiness030217 neurology & neurosurgeryRespiratory minute volumeComputers in biology and medicine
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Basic cardiovascular variability signals: mutual directed interactions explored in the information domain.

2017

The study of short-term cardiovascular interactions is classically performed through the bivariate analysis of the interactions between the beat-to-beat variability of heart period (RR interval from the ECG) and systolic blood pressure (SBP). Recent progress in the development of multivariate time series analysis methods is making it possible to explore how directed interactions between two signals change in the context of networks including other coupled signals. Exploiting these advances, the present study aims at assessing directional cardiovascular interactions among the basic variability signals of RR, SBP and diastolic blood pressure (DBP), using an approach which allows direct compar…

MaleMultivariate statisticsAdolescentPhysiologySystole0206 medical engineeringBiomedical EngineeringBiophysicsContext (language use)Blood Pressure02 engineering and technologyBivariate analysisBaroreflex03 medical and health sciencesElectrocardiography0302 clinical medicineinformation domainDiastoleHeart RatePhysiology (medical)StatisticsHumansbaroreflexMathematicsResting state fMRIheart rate variabilityMultivariate time series analysiscomplex system020601 biomedical engineeringcardiovascular oscillationBlood pressureBiophysicInformation domainSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaFemaleblood pressure variability030217 neurology & neurosurgeryHumancirculatory and respiratory physiologyPhysiological measurement
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ANALYSIS OF RESPIRATORY SINUS ARRHYTHMIA MECHANISMS IN INFORMATION DOMAIN

2018

medicine.medical_specialtybusiness.industryPathology and Forensic Medicine03 medical and health sciences0302 clinical medicine030228 respiratory systemInformation domainPhysiology (medical)Internal medicinemedicineCardiologyVagal tonebusiness030217 neurology & neurosurgeryPathophysiology
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Information domain analysis of respiratory sinus arrhythmia mechanisms.

2019

Ventilation related heart rate oscillations – respiratory sinus arrhythmia (RSA) – originate in human from several mechanisms. Two most important of them – the central mechanism (direct communication between respiratory and cardiomotor centers), and the peripheral mechanism (ventilation-associated blood pressure changes transferred to heart rate via baroreflex) have been described in previous studies. The major aim of this study was to compare the importance of these mechanisms in the generation of RSA non-invasively during various states by quantifying the strength of the directed interactions between heart rate, systolic blood pressure and respiratory volume signals. Seventy-eight healthy…

AdultMalemedicine.medical_specialtySupine positionAdolescentPhysiologyBlood Pressure030204 cardiovascular system & hematologyBaroreflex03 medical and health sciencesOrthostatic vital signsElectrocardiographyYoung Adult0302 clinical medicineHeart RateInternal medicineHeart ratemedicineHumansInformation measurePhotoplethysmographybusiness.industryHead-up tiltCardio-respiratory couplingCardiorespiratory fitnessGeneral MedicineBaroreflexRespiratory Sinus ArrhythmiaBlood pressureCardiologyBreathingFemalebusiness030217 neurology & neurosurgeryRespiratory minute volumePhysiological research
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Causal analysis of short-term cardiovascular variability: state-dependent contribution of feedback and feedforward mechanisms.

2016

Baroreflex function is usually assessed from spontaneous oscillations of blood pressure (BP) and cardiac RR interval assuming a unidirectional influence from BP to RR. However, the interaction of BP and RR is bidirectional—RR also influences BP. Novel methods based on the concept of Granger causality were recently developed for separate analysis of feedback (baroreflex) and feedforward (mechanical) interactions between RR and BP. We aimed at assessing the proportion of the two causal directions of the interactions between RR and systolic BP (SBP) oscillations during various conditions, and at comparing causality measures from SBP to RR with baroreflex gain indexes. Arterial BP and ECG sig…

medicine.medical_specialtySupine position0206 medical engineeringBiomedical EngineeringBlood Pressure02 engineering and technologyBaroreflex03 medical and health sciencesElectrocardiographyYoung Adult0302 clinical medicineInternal medicineHeart ratemedicineSupine PositionHumanscardiovascular diseasesSimulationFeedback PhysiologicalHead-up tiltFeed forwardComputer Science Applications1707 Computer Vision and Pattern RecognitionSignal Processing Computer-AssistedBaroreflex020601 biomedical engineeringCausalityComputer Science ApplicationsTerm (time)Blood pressureMental arithmeticState dependentSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaGranger causalityCardiologyInformation domainPsychology030217 neurology & neurosurgeryStress Psychologicalcirculatory and respiratory physiologyMedicalbiological engineeringcomputing
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