Search results for "Heart rate Variability"

showing 10 items of 232 documents

Impaired circadian heart rate variability in Parkinson’s disease: a time-domain analysis in ambulatory setting

2020

Abstract Background Heart rate variability (HRV) decreases in Parkinson’s disease (PD) and it can be considered a marker for cardiovascular dysautonomia. The purpose of this pilot study is to evaluate long-term time-domain analysis of HRV of PD patients and compare the results with those of matched healthy individuals. Methods Idiopathic PD patients without comorbidity impairing HRV, and age-matched healthy individuals were recruited in a pilot study. A long-term time domain analysis of HRV using 24-h ambulatory ECG was performed. Results Overall, 18 PD patients fulfilling inclusion criteria completed the evaluation (mean age was 55.6 ± 8.8, disease duration: 5.0 ± 4.7). Mean SCOPA-AUT scor…

Autonomic disordersmedicine.medical_specialtyParkinson's diseaseNeurologyAutonomic disorderPopulationPilot ProjectsNon-motor symptomsPrimary DysautonomiasAutonomic disorderlcsh:RC346-429Antiparkinson AgentsLevodopaHeart RateInternal medicinemedicineHumansHeart rate variabilityeducationlcsh:Neurology. Diseases of the nervous systemAgededucation.field_of_studybusiness.industryDysautonomiaParkinson DiseaseGeneral MedicineMiddle Agedmedicine.diseaseComorbidityCircadian RhythmHeart rate variability SCOPA-AUTCardiovascular DiseasesAmbulatoryCardiologyNeurology (clinical)medicine.symptombusinessResearch ArticleBMC Neurology
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Heart rate variability changes at 2400 m altitude predicts acute mountain sickness on further ascent at 3000-4300 m altitudes

2012

Objective: If the body fails to acclimatize at high altitude, acute mountain sickness (AMS) may result. For the early detection of AMS, changes in cardiac autonomic function measured by heart rate variability (HRV) may be more sensitive than clinical symptoms alone. The purpose of this study was to ascertain if the changes in HRV during ascent are related to AMS. Methods: We followed Lake Louise Score (LLS), arterial oxygen saturation at rest (R-SpO2) and exercise (Ex-SpO2) and HRV parameters daily in 36 different healthy climbers ascending from 2400 m to 6300 m altitudes during five different expeditions. Results: After an ascent to 2400 m, root mean square successive differences, high-fre…

Autonomic functionmedicine.medical_specialtySupine positionPhysiologymountaineeringheart rate variationEarly detection030204 cardiovascular system & hematologyAcclimatizationlcsh:Physiology03 medical and health sciences0302 clinical medicineAltitudemountain sicknessPhysiology (medical)Internal medicinemedicineHeart rate variabilityOriginal Research Articlelcsh:QP1-981business.industryHeart rate variationaltitude illness030229 sport sciencesextreme altitudeEffects of high altitude on humans3121 General medicine internal medicine and other clinical medicineCardiologybusiness
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Effects of anxiety during mental arithmetic stress on heart rate variability in healthy subjects

2011

Aim: Anxiety may cause an increased risk of myocardial infarction by reductions in heart rate variability (HRV). However, no data exists on the effect of anxiety on a standard mental test of HRV. The aim of this study was to evaluate the association between anxiety elicited by mental stress and HRV. Methods: Effect of anxiety in the actual state (A-State) and in everyday life (A-Trait) has been assessed in 13 healthy subjects and its association to low (LF) and high-frequency (HF) of HRV during mental arithmetic stress has been tested through correlation analysis. Results: A significant increase from baseline through arithmetic stress was observed in the LF component (LF(nu) from 56.87 ± 4.…

Autonomic nervous systemMental arithmetic stressSettore M-EDF/01 - Metodi E Didattiche Delle Attivita' MotorieSettore BIO/09 - FisiologiaHeart rate variability
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Predictability decomposition detects the impairment of brain-heart dynamical networks during sleep disorders and their recovery with treatment

2016

This work introduces a framework to study the network formed by the autonomic component of heart rate variability (cardiac process η ) and the amplitude of the different electroencephalographic waves (brain processes δ , θ , α , σ , β ) during sleep. The framework exploits multivariate linear models to decompose the predictability of any given target process into measures of self-, causal and interaction predictability reflecting respectively the information retained in the process and related to its physiological complexity, the information transferred from the other source processes, and the information modified during the transfer according to redundant or synergistic interaction betwee…

Autonomic nervous system; Brain-heart interactions; Delta sleep electroencephalogram; Granger causality; Heart rate variability; Synergy and redundancy; Mathematics (all); Engineering (all); Physics and Astronomy (all)General MathematicsGeneral Physics and AstronomyElectroencephalography01 natural sciencesSynergy and redundancy03 medical and health sciencesPhysics and Astronomy (all)0302 clinical medicineEngineering (all)0103 physical sciencesMedicineHeart rate variabilityAutonomic nervous systemMathematics (all)Predictability010306 general physicsHeart rate variabilityCardiac processmedicine.diagnostic_testbusiness.industryGeneral EngineeringHealthy subjectsBrainArticlesAutonomic nervous systemDelta sleep electroencephalogramSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaGranger causalityBrain-heart interactionSleep (system call)businessNeuroscience030217 neurology & neurosurgery
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Assessment of Granger causality by nonlinear model identification: application to short-term cardiovascular variability.

2007

A method for assessing Granger causal relationships in bivariate time series, based on nonlinear autoregressive (NAR) and nonlinear autoregressive exogenous (NARX) models is presented. The method evaluates bilateral interactions between two time series by quantifying the predictability improvement (PI) of the output time series when the dynamics associated with the input time series are included, i.e., moving from NAR to NARX prediction. The NARX model identification was performed by the optimal parameter search (OPS) algorithm, and its results were compared to the least-squares method to determine the most appropriate method to be used for experimental data. The statistical significance of…

Biomedical EngineeringBlood PressureBivariate analysisDirectionalitySensitivity and SpecificitySurrogate dataFeedbackNonlinear parametric modelGranger causalityControl theoryHeart RateOptimal parameter searchStatisticsAnimalsHumansComputer SimulationPredictabilityHeart rate variabilityMathematicsNonlinear autoregressive exogenous modelCardiovascular regulationSystem identificationModels CardiovascularNonlinear systemAutoregressive modelNonlinear DynamicsAutoregressive exogenous modelSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaRegression AnalysisSurrogate dataArterial pressure variabilityAlgorithmsAnnals of biomedical engineering
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Bivariate nonlinear prediction to quantify the strength of complex dynamical interactions in short-term cardiovascular variability.

2005

A nonlinear prediction method for investigating the dynamic interdependence between short length time series is presented. The method is a generalization to bivariate prediction of the univariate approach based on nearest neighbor local linear approximation. Given the input and output series x and y, the relationship between a pattern of samples of x and a synchronous sample of y was approximated with a linear polynomial whose coefficients were estimated from an equation system including the nearest neighbor patterns in x and the corresponding samples in y. To avoid overfitting and waste of data, the training and testing stages of the prediction were designed through a specific out-of-sampl…

Bivariate time seriePhysics::Medical PhysicsBiomedical EngineeringBlood PressureBivariate analysisOverfittingCross-validationk-nearest neighbors algorithmCardiovascular Physiological PhenomenaHealth Information ManagementHeart RateTilt-Table TestStatisticsApplied mathematicsHumansComputer SimulationPredictabilityHeart rate variabilityMathematicsHealth InformaticBaroreflex controlSystolic arterial pressure variabilityUnivariateModels CardiovascularNonlinear predictionComputer Science Applications1707 Computer Vision and Pattern RecognitionComputer Science ApplicationsNonlinear systemComputational Theory and MathematicsNonlinear DynamicsLinear approximationMedicalbiological engineeringcomputing
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Long-term parameters of heart rate variability in patients with insulin-resistance.

2019

Heart rate variability (HRV) is defined as the oscillation in both the interval between consecutive heartbeats (considered RR intervals) and consecutives measures of instantaneous heart rates.1 HRV measures the cardiac autonomic function noninvasively1,2 and its reduction is an independent risk factor for cardiovascular events.3 Insulin-resistance is a pathological condition, in which the body’s cells become resistant to insulin effects.4 The aim of our study was to evaluate the relationship between insulin-resistance and the reduction of HRV parameters.

Blood GlucoseMalemedicine.medical_specialtyTime FactorsMEDLINEPilot ProjectsHeart rate variability insulin-resistanceInsulin resistanceHeart RateInternal medicineHeart ratemedicineHeart rate variabilityHumansInsulinIn patientAgedRetrospective StudiesMetabolic SyndromeInsulin bloodbusiness.industryRetrospective cohort studyGeneral MedicineMiddle Agedmedicine.diseaseTerm (time)CardiologyFemaleInsulin ResistanceCardiology and Cardiovascular MedicinebusinessBiomarkersJournal of cardiovascular medicine (Hagerstown, Md.)
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Associations of cardiometabolic risk factors with heart rate variability in 6‐ to 8‐year‐old children: The PANIC Study

2019

BACKGROUND Associations of cardiometabolic risk factors with heart rate variability (HRV) in children are unclear. We examined associations of cardiometabolic risk score (CRS) and individual cardiometabolic risk factors with HRV variables in 6- to 8-year-olds. METHODS The participants were a population-based sample of 443 children participating in baseline measurements of the Physical Activity and Nutrition in Children trial. Cardiometabolic risk factors included waist circumference (WC), insulin, glucose, triglycerides, HDL cholesterol, systolic blood pressure (SBP), and diastolic blood pressure (DBP). CRS was calculated as WC + insulin + glucose + triglycerides - HDL cholesterol + the mea…

Blood GlucoseMalemedicine.medical_specialtyWaistEndocrinology Diabetes and Metabolismmedicine.medical_treatmentPopulationBlood Pressurechemistry.chemical_compoundHeart RateInternal medicineotorhinolaryngologic diseasesInternal MedicinemedicineHumansInsulinHeart rate variabilityChildeducationeducation.field_of_studyCholesterolbusiness.industryInsulinCardiometabolic Risk FactorsCardiorespiratory fitnessmedicine.diseaseCross-Sectional StudiesBlood pressurechemistryPediatrics Perinatology and Child HealthCardiologyFemaleMetabolic syndromebusinesscirculatory and respiratory physiologyPediatric Diabetes
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Blood pressure and cardiac autonomic nervous system in obese type 2 diabetic patients: effect of metformin administration

2004

Background: Hyperinsulinemia/insulin resistance and elevated plasma free fatty acids (FFA) levels are involved in the hypertension and cardiac sympathetic overactivity. Metformin improves insulin action and lower plasma FFA concentrations. We investigate the possible effect of metformin on arterial blood pressure (BP) and cardiac sympathetic nervous system. Methods: One hundred twenty overweight type 2 diabetic patients were treated by placebo (n = 60) + diet or metformin (850 mg twice daily) (n = 60) + diet for 4 months, to evaluate the effect of metformin treatment on the cardiac autonomic nervous system. Insulin resistance was measured by the Homeostasis Model Assessment (HOMA) index. He…

Blood GlucoseMalemedicine.medical_specialtyendocrine system diseasesmedicine.medical_treatmentBlood PressureType 2 diabetesFatty Acids NonesterifiedAutonomic Nervous SystemInsulin resistanceHeart RateDiabetes mellitusInternal medicineInternal MedicineHyperinsulinemiaDiabetes MellitusMedicineHumansHypoglycemic AgentsObesityHeart rate variabilityTriglyceridesAgedGlycated HemoglobinFree fatty acidAnthropometrybusiness.industryInsulinnutritional and metabolic diseasesInsulin resistanceMiddle Agedmedicine.diseaseMetforminMetforminEndocrinologyBlood pressureTreatment OutcomeDiabetes Mellitus Type 2Multivariate AnalysisFemalebusinessHyperinsulinismBiomarkersmedicine.drug
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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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