Search results for "Heart"

showing 10 items of 3201 documents

Associations between success and failure in a face-to-face competition and psychobiological parameters in young women

2012

Within an evolutionary framework, in recent years some questions have been raised about whether women have a pattern of psychobiological response to social stress similar to that described in men. The main objective of this study was to analyze women's patterns of neuroendocrine, cardiovascular and mood responses to an individual competitive task, taking into account the outcome obtained. For this purpose, we measured salivary testosterone (T) and cortisol (C) levels, heart rate (HR) and blood pressure (BP), in addition to mood changes, in 40 healthy young women before, during and after a face-to-face laboratory competition. We also assessed some relevant psychological traits. Our results i…

Competitive BehaviorHydrocortisoneEndocrinology Diabetes and MetabolismBlood PressureAffect (psychology)Developmental psychologyYoung AdultEndocrinologyHeart RateAdaptation PsychologicalHeart rateHumansTestosteroneWomenYoung adultSalivaBiological PsychiatrySocial stressEndocrine and Autonomic SystemsTestosterone (patch)AffectPsychiatry and Mental healthBlood pressureMoodFollicular PhaseChallenge hypothesisFemalePsychologyStress PsychologicalPsychoneuroendocrinology
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Towards High Resolution Computational Models of the Cardiac Conduction System: A Pipeline for Characterization of Purkinje-Ventricular-Junctions

2011

The cardiac conduction system (CCS) has been in the spot light of the clinical and modeling community in recent years because of its fundament role in physiology and pathophysiology of the heart. Experimental research has focused mainly on investigating the electrical properties of the Purkinje-ventricular-junctions (PVJs). The structure of the PVJs has only been described through schematic drawings but not thoroughly studied. In this work confocal microscopy was used with the aim of three-dimensional characterization of PVJs. Adult rabbit hearts were labeled with fluorescent dyes, imaged with confocal microscopy and Purkinje fibers differentiated from other cardiac tissue by their lack of …

Computational modelMaterials sciencePurkinje fibersCardiac electrophysiologyPipeline (computing)Resolution (electron density)Anatomylaw.inventionmedicine.anatomical_structureConfocal microscopylawRegion growingmedicineElectrical conduction system of the heartBiomedical engineering
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Pain fingerprinting using multimodal sensing: pilot study

2021

Abstract Pain is a complex phenomenon, the experience of which varies widely across individuals. At worst, chronic pain can lead to anxiety and depression. Cost-effective strategies are urgently needed to improve the treatment of pain, and thus we propose a novel home-based pain measurement system for the longitudinal monitoring of pain experience and variation in different patients with chronic low back pain. The autonomous nervous system and audio-visual features are analyzed from heart rate signals, voice characteristics and facial expressions using a unique measurement protocol. Self-reporting is utilized for the follow-up of changes in pain intensity, induced by well-designed physical …

Computer Networks and Communicationskipusignaalianalyysimonitorointiaudio analysiskivunhoitomachine learningkoneoppiminenHardware and Architectureheart rateMedia Technologyselkäkrooninen kipuilmeetEEGsykemittaritlow back painfacial expressionelectroencephalographySoftwareMultimedia Tools and Applications
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Estimation of confidence limits for descriptive indexes derived from autoregressive analysis of time series: Methods and application to heart rate va…

2017

The growing interest in personalized medicine requires making inferences from descriptive indexes estimated from individual recordings of physiological signals, with statistical analyses focused on individual differences between/within subjects, rather than comparing supposedly homogeneous cohorts. To this end, methods to compute confidence limits of individual estimates of descriptive indexes are needed. This study introduces numerical methods to compute such confidence limits and perform statistical comparisons between indexes derived from autoregressive (AR) modeling of individual time series. Analytical approaches are generally not viable, because the indexes are usually nonlinear funct…

Computer and Information SciencesStatistical methodsConfidence Intervals; Humans; Monte Carlo Method; Regression Analysis; Heart Rate; Biochemistry Genetics and Molecular Biology (all); Agricultural and Biological Sciences (all)EntropyCardiologylcsh:MedicineResearch and Analysis MethodsSystems ScienceRegression AnalysiHeart RateConfidence IntervalsMedicine and Health SciencesHumanslcsh:ScienceBiochemistry Genetics and Molecular Biology (all)Simulation and ModelingPhysicslcsh:RProbability TheoryMonte Carlo methodAgricultural and Biological Sciences (all)Nonlinear DynamicsWhite NoiseSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaPhysical SciencesSignal ProcessingMathematical and statistical techniquesThermodynamicsEngineering and TechnologyRegression Analysislcsh:QConfidence IntervalMathematicsStatistics (Mathematics)HumanResearch ArticleStatistical DistributionsPLoS ONE
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Are nonlinear model-free conditional entropy approaches for the assessment of cardiac control complexity superior to the linear model-based one?

2016

Objective : We test the hypothesis that the linear model-based (MB) approach for the estimation of conditional entropy (CE) can be utilized to assess the complexity of the cardiac control in healthy individuals. Methods : An MB estimate of CE was tested in an experimental protocol (i.e., the graded head-up tilt) known to produce a gradual decrease of cardiac control complexity as a result of the progressive vagal withdrawal and concomitant sympathetic activation. The MB approach was compared with traditionally exploited nonlinear model-free (MF) techniques such as corrected approximate entropy, sample entropy, corrected CE, two k -nearest-neighbor CE procedures and permutation CE. Electroca…

Computer scienceEntropyBiomedical EngineeringSensitivity and Specificity01 natural sciencesApproximate entropy03 medical and health sciencesEntropy (classical thermodynamics)0302 clinical medicineHeart RateHeart Rate Determination0103 physical sciencesStatisticsHumansEntropy (information theory)Autonomic nervous systemComputer SimulationEntropy (energy dispersal)010306 general physicsEntropy (arrow of time)Heart rate variabilityFeedback PhysiologicalConditional entropyEntropy (statistical thermodynamics)Head-up tiltModels CardiovascularLinear modelCardiovascular regulationReproducibility of ResultsHeartStatistical modelMutual informationSample entropyMutual informationNonlinear DynamicsConcomitantSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaLinear ModelsAlgorithmRandom variableAlgorithms030217 neurology & neurosurgeryEntropy (order and disorder)
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Advanced computation in cardiovascular physiology: New challenges and opportunities

2021

Recent developments in computational physiology have successfully exploited advanced signal processing and artificial intelligence tools for predicting or uncovering characteristic features of physiological and pathological states in humans. While these advanced tools have demonstrated excellent diagnostic capabilities, the high complexity of these computational 'black boxes’ may severely limit scientific inference, especially in terms of biological insight about both physiology and pathological aberrations. This theme issue highlights current challenges and opportunities of advanced computational tools for processing dynamical data reflecting autonomic nervous system dynamics, with a speci…

Computer scienceGeneral MathematicsComputationGeneral Physics and AstronomyelectrocardiogramMachine learningcomputer.software_genreComputer-AssistedHeart RateArtificial IntelligenceHumansInterpretabilitySignal processingbusiness.industryDeep learningGeneral Engineeringheart rate variabilitydeep learningSignal Processing Computer-Assistedcardiology; deep learning; electrocardiogram; heart rate variability; interpretability; respiration; Heart Rate; Humans; Nonlinear Dynamics; Signal Processing Computer-Assisted; Algorithms; Artificial IntelligenceCardiovascular physiologyComputational physiologyNonlinear DynamicscardiologySignal ProcessingArtificial intelligencebusinessinterpretabilitycomputerrespirationAlgorithms
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Computational issues in fitting joint frailty models for recurrent events with an associated terminal event.

2020

Abstract Background and objective: Joint frailty regression models are intended for the analysis of recurrent event times in the presence of informative drop-outs. They have been proposed for clinical trials to estimate the effect of some treatment on the rate of recurrent heart failure hospitalisations in the presence of drop-outs due to cardiovascular death. Whereas a R-software-package for fitting joint frailty models is available, some technical issues have to be solved in order to use SASⓇ 1 software, which is required in the regulatory environment of clinical trials. Methods: First, we demonstrate how to solve these issues by deriving proper likelihood-decompositions, in particular fo…

Computer scienceHealth InformaticsMachine learningcomputer.software_genre030218 nuclear medicine & medical imaging03 medical and health sciences0302 clinical medicineLinear regressionHumansComputer SimulationEvent (probability theory)ProbabilityProportional Hazards ModelsHeart FailureLikelihood FunctionsFrailtybusiness.industryModels CardiovascularReproducibility of ResultsRegression analysisConfidence intervalComputer Science ApplicationsHospitalizationTransformation (function)Data Interpretation StatisticalMultivariate AnalysisArtificial intelligencebusinesscomputer030217 neurology & neurosurgeryAlgorithmsSoftwareComputer methods and programs in biomedicine
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Automatic left ventricle volume calculation with explainability through a deep learning weak-supervision methodology

2021

[EN] Background and objective: Magnetic resonance imaging is the most reliable imaging technique to assess the heart. More specifically there is great importance in the analysis of the left ventricle, as the main pathologies directly affect this region. In order to characterize the left ventricle, it is necessary to extract its volume. In this work we present a neural network architecture that is capable of directly estimating the left ventricle volume in short axis cine Magnetic Resonance Imaging in the end-diastolic frame and provide a segmentation of the region which is the basis of the volume calculation, thus offering explain-ability to the estimated value. Methods: The network was des…

Computer scienceHeart VentriclesMagnetic Resonance Imaging CineHealth InformaticsWeak supervisionTECNOLOGIA ELECTRONICAsymbols.namesakeMagnetic resonance imagingSegmentationApproximation errorImage Processing Computer-AssistedHumansSegmentationBasis (linear algebra)Artificial neural networkbusiness.industryDeep learningPattern recognitionHeartDeep learningLeft ventricleExplainabilityPearson product-moment correlation coefficientComputer Science ApplicationsTest setsymbolsArtificial intelligenceNeural Networks ComputerbusinessSoftwareVolume (compression)
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A preliminary investigation of the effect of contact pressure on the accuracy of heart rate monitoring by wearable PPG wrist band

2019

The increase of safety and health monitor of workers has become a crucial objective to prevent excessive physical workloads, injuries, accidents and errors. Heart rate (HR) is a very important physiological indicator which could properly describe the workers’ physical status. Recently, wearable photoplethysmographic (PPG) wristband trackers have been utilized to measure HR without hindering normal gesture of workers. However, the quality of PPG signals is highly affected by human physical motions, resulting in a poor reliable HR estimation. Specifically, during different activities and gestures, PPG sensor contact pressures may have an impact on the quality of the heart rate signal. To appr…

Computer sciencePhotoplethysmography wearable sensor PPG sensor contact pressureWearable computerSettore ING-IND/34 - Bioingegneria IndustrialeWristSignalLoad cellSettore ING-IND/14 - Progettazione Meccanica E Costruzione Di Macchinemedicine.anatomical_structureHeart rate monitoringHeart ratemedicineSettore ING-IND/12 - Misure Meccaniche E TermicheHeart rate variabilitysense organsContact pressureBiomedical engineering
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Measurement, Prediction, and Control of Individual Heart Rate Responses to Exercise-Basics and Options for Wearable Devices.

2018

The use of wearable devices or "wearables" in the physical activity domain has been increasing in the last years. These devices are used as training tools providing the user with detailed information about individual physiological responses and feedback to the physical training process. Advantages in sensor technology, miniaturization, energy consumption and processing power increased the usability of these wearables. Furthermore, available sensor technologies must be reliable, valid, and usable. Considering the variety of the existing sensors not all of them are suitable to be integrated in wearables. The application and development of wearables has to consider the characteristics of the p…

Computer scienceProcess (engineering)Physiologyheart rate control0206 medical engineeringControl (management)Wearable computerphenomenological approaches02 engineering and technologyReviewUSablelcsh:Physiology03 medical and health sciences0302 clinical medicineheart rate predictionHuman–computer interactionPhysiology (medical)training monitoringWearable technologyheart rate modelinglcsh:QP1-981business.industrywearable sensorsUsability030229 sport sciencesEnergy consumption020601 biomedical engineeringVariety (cybernetics)load controlddc:004businessFrontiers in physiology
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