Associations Of Heart Rate Variability Measured During Orthostatic Test And During Daily Routine Activities

2017 ◽  
Vol 49 (5S) ◽  
pp. 156
Author(s):  
Ricardo Mesquita ◽  
Heikki Kyröläinen ◽  
Daniela S. Olstad
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Routine Activities ◽  
Daily Routine ◽  
Orthostatic Test

scholarly journals Reliability and validity of time domain heart rate variability during daily routine activities – an alternative to the morning orthostatic test?

2017 ◽  
Vol 9 (1) ◽  
pp. 64-68 ◽  
Author(s):  
Ricardo Neves de Oliveira Mesquita ◽  
Heikki Kyröläinen ◽  
Daniela Schäfer Olstad
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Time Domain ◽  
Reliability And Validity ◽  
Routine Activities ◽  
Daily Routine ◽  
Orthostatic Test ◽  
Rr Intervals ◽  
White Collar Workers ◽  
Mean Square Difference

SummaryStudy aim: To determine the reliability and validity of a time domain heart rate variability (HRV) index during free-living physical activity (FLPA).Material and methods: Eight white-collar workers participated in this study. RR intervals (time between consecutive R-peaks of the PQRS complex) were recorded using the Polar V800 heart rate (HR) monitor upon awakening and at work on 16 different days. A total of 127 cycles of sitting periods followed by walking breaks were included for consecutive pairwise analysis for reliability. The HR values from the orthostatic test (OT) were compared with the corresponding values at work.Results: The HR values showed high levels of repeatability [the coefficient of variation (CV) during sitting and walking at work was 4.71 and 3.99%, respectively, with a typical error (TE) of 3.73 (3.34-4.25) and 3.65 (3.31-4.09)], but they did not correlate with the corresponding OT HR upon awakening (r = 0.28 for supine vs. sitting and r = 0.05 for standing vs. walking, p > 0.05). The root-mean-square difference of successive normal RR (RMSSD) was revealed not to be repeatable [CV values during sitting and walking were 19.99 and 29.05%, respectively, with a TE of 7.9 (7.15-8.85) and 9.43 (8.53-10.57)].Conclusions: Analyzing RMSSD from daily routine activities was not reliable, and therefore validity cannot be assumed. RMSSD should therefore be calculated from RR intervals recorded in standardized conditions, such as during the OT upon awakening.

scholarly journals Features of heart rate variability in patients with takotsubo syndrome

2021 ◽  
Vol 10 (Supplement_1) ◽  
Author(s):  
D Evdokimov ◽  
SA Boldueva ◽  
VS Feoktistova ◽  
TA Baeva
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Sinus Rhythm ◽  
Autonomic Regulation ◽  
Deep Breathing ◽  
Takotsubo Syndrome ◽  
Orthostatic Test ◽  
Rate Regulation ◽  
Heart Rate Regulation ◽  
Deep Breathing Test

Abstract Funding Acknowledgements Type of funding sources: None. Main funding source(s): North-Western State Medical University named after I.I. Mechnikov Objective to study the features of autonomic regulation of sinus rhythm features of autonomic regulation of cardiac sinus rhythm in patients with Takotsubo syndrome (TTS) during inpatient stay in hospital. Materials and methods. The study included 25 female patients (the median age 57.5 ± 28.5 years) with TTS, diagnosis was based on the InterTAK criteria. On the 5-7th day after admission, the heart rate variability (HRV) was assessed both at rest and cardiac autonomic function tests: the deep breathing test (DBT) and active orthostatic test (AOT) with the usage of a computer diagnostic system «Valenta». RESULTS According to HRV data, initially at rest, the majority of the studied patients predominantly had a parasympathetic impact on the heart rate regulation: in 70% - increased parasympathetic influence, in 17% - increased sympathetic influence, in 13% - a balanced heart rate regulation. When performing a DBT, the predominance of the parasympathetic influence on the heart rate was noted both in spectral parameters and according to the data of time analysis (HF  during DBT  increased 1.8 times  up to  489.6 ± 114.2 ms2 (p <0.05) ; LF  decreased 1.7 times  up to 254.1 ± 70.3 ms2 (p <0.05); VLF  increased 2.8 times up to 402.3 ± 101.8 ms2 (p <0, 05); TP  increased 1.4 times up to 1145.9 ± 251.3 ms2; CV increased 1.3 times up to 6.5 ± 0.7% (p <0.05); SDNN increased 1.3 times up to - 58.7 ± 6.6 ms (p <0.05). HRV measured during an AOT  showed a paradoxical  evaluation  in the parasympathetic impact on the heart rate (HF increased by 1.8 times and reached - 488.0 ± 104.7 ms2 (p <0.05); LF decreased by 1.1 times up to  408 , 4 ± 103.6 ms2; VLF increased 1.2 times  up to  166.4 ± 52.2 ms2; TP increased 1.3 times  up to 1062.8 ± 181.1 ms2 (p <0.05); CV increased 1.6 times  up to 8.0 ± 0.9% (p <0.05); SDNN increased 1.4 times  up to 62.6 ± 7.5 ms (p <0.05)). Conclusions During the index hospital inpatient stays the majority of patients with TTS have a vegetative imbalance due to increased parasympathetic influence on the heart rate, both at rest and  during a deep breathing test and an active orthostatic test. This fact is quite unexpected and requires further study.

Heart rate variability in young hockey players at rest and during active orthostatic test

2014 ◽  
Vol 40 (2) ◽  
pp. 207-213 ◽  
Author(s):  
I. Ya. Lutfullin ◽  
R. R. Almetova
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Orthostatic Test ◽  
Hockey Players

scholarly journals A novel approach in heart-rate-variability analysis

2021 ◽  
Author(s):  
Andras Buzas ◽  
Tamas Horvath ◽  
Andras Der
Keyword(s):  
Heart Rate ◽  
Time Series ◽  
Heart Rate Variability ◽  
Extended Period ◽  
Evaluation Procedure ◽  
Heart Rate Variability Analysis ◽  
Daily Routine ◽  
Poincaré Plot ◽  
Statistical Measures ◽  
Registration Period

Heart-rate variability (HRV), measured by the fluctuation of beat-to-beat intervals, has been growingly considered the most important hallmark of heart rate (HR) time series. HRV can be characterized by various statistical measures both in the time and frequency domains, or by nonlinear methods. During the past decades, an overwhelming amount of HRV data has been piled up in the research community, but the individual results are difficult to reconcile due to the different measuring conditions and the usually HR-dependent statistical HRV-parameters applied. Moreover, the precise HR-dependence of HRV parameters is not known. Using data gathered by a wearable sensor of combined heart-rate and actigraphy modalities, here, we introduce a novel descriptor of HRV, based on a modified Poincare plot of 24-h RR-recordings. We show that there exists a regressive biexponential HRV versus HR master curve (M-curve) that is highly conserved for a healthy individual on short and medium terms (on the hours to months scale, respectively). At the same time, we reveal how this curve is related to age in the case of healthy people, and establish alterations of the M-curves of heart-attack patients. A stochastic neuron model accounting for the observed phenomena is also elaborated, in order to facilitate physiological interpretation of HRV data. Our novel evaluation procedure applied on the time series of interbeat intervals allows the description of the HRV(HR) function with unprecedented precision. To utilize the full strength of the method, we suggest a 24-hour-long registration period under natural, daily-routine circumstances (i.e., no special measuring conditions are required). By establishing a patient's M-curve, it is possible to monitor the development of his/her status over an extended period of time. On these grounds, the new method is suggested to be used as a competent tool in future HRV analyses for both clinical and training applications, as well as for everyday health promotion.

Autonomic regulation in the major depression during SSRI antideperssant treatment

2011 ◽  
Vol 26 (S2) ◽  
pp. 600-600
Author(s):  
O. Antipova
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Major Depression ◽  
Rating Scale ◽  
Evaluation Criteria ◽  
Autonomic Regulation ◽  
Control Group ◽  
Functional Evaluation ◽  
Autonomic Reactivity ◽  
Orthostatic Test

IntroductionImportance of current research is determined by the need to find the clinical and functional evaluation criteria for the systemic patterns of changes in physiological reactivity of the patient at various stages depression treatment.ObjectiveOptimization of diagnostics and planning of treatment of patients with depression based on analysis psychopathological state and autonomic reactivity during active treatment using SSRI antidepressants.AimsSystem analyze of clinical-psychopathological characteristics and autonomic reactivity of major depression. Main group included 62 patients with the diagnosis of depressive episode. Control group: 64 healthy persons.MethodsClinico- psychopathological, clinico- anamnestic, Hamilton Depression Rating Scale (HDRS-17), the analysis of heart rate variability for investigation of autonomic regulation.Results of the depressive patients autonomic regulation study show the reduction of total heart rate variability is observed at rest and in orthostatic test. The balance of sympathetic, parasympathetic and suprasegmental parts of autonomic nervous system was preserved at rest in depression. However after orthostatic test the activity of sympathetic baroreflex mechanisms is decreased and the hyperactivation of suprasegmental ergotropic systems is revealed. During the 4–6-weeks treatment the positive dynamics of psychopathological characteristics is observed but the changes of autonomic reactivity are not revealed. After 6-months therapy only 30, 6% of patients demonstrate signs of normalisation of autonomic regulation.ConclusionsObtained data, apparently, attest to the fact that the emotional and autonomic symptoms are restored with different speed. The results of study should be used in the planning of treatment in the psychiatric practice and in the primary medical care.

Frequency characteristics of long-term heart rate variability during constant-routine protocol

2003 ◽  
Vol 285 (1) ◽  
pp. R171-R176 ◽  
Author(s):  
Naoko Aoyagi ◽  
Kyoko Ohashi ◽  
Yoshiharu Yamamoto
Keyword(s):  
Physical Activity ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Spectral Analysis ◽  
Core Body Temperature ◽  
Coarse Graining ◽  
Daily Routine ◽  
Crossover Frequency ◽  
Behavioral Factors

The effects of such behavioral factors as physical activity, food intake, and circadian rhythm on long-term heart rate variability (HRV) in humans remain poorly understood. We therefore studied their effects on HRV using a constant-routine protocol that included simultaneous core body temperature (CBT) correction. Seven healthy subjects completed the constant-routine and daily-routine protocols, during which HRV and CBT were continuously monitored. During the constant routine, subjects were kept awake for 27 h in a semirecumbent posture with minimal physical activity; small isocaloric meals were provided every 2 h. During the daily routine, subjects carried on their lives normally. Data were analyzed using generic spectral analysis based on a fast Fourier transform; coarse-graining spectral analysis was also used to eliminate periodicity due to the regular meals for raw HRV and for the CBT-corrected HRV without circadian and/or low-frequency ultradian components. The results showed that 1) the power spectra of HRV in the constant routine and daily routine had similar power-law scalings at frequencies above ∼10-3.5 Hz, while 2) below that crossover frequency, HRV was smaller in the constant routine than in the daily routine, with the difference becoming significant ( P < 0.05) at <10-4 Hz, 3) coarse-graining spectral analysis eliminated diet-induced peaks in generic spectral analysis-based HRV spectra during the constant routine and emphasized the crossover at ∼10-3.5 Hz, and 4) CBT correction did not alter the results. Below a frequency of ∼10-3.5 Hz (a period >1 h), HRV is strongly influenced by behavioral factors; above that crossover frequency, HRV is behavior independent, possibly reflecting an intrinsic regulatory system.

scholarly journals Noninvasive Glucose Measurement Using Machine Learning and Neural Network Methods and Correlation with Heart Rate Variability

2020 ◽  
Vol 2020 ◽  
pp. 1-13 ◽  
Author(s):  
Marjan Gusev ◽  
Lidija Poposka ◽  
Gjoko Spasevski ◽  
Magdalena Kostoska ◽  
Bojana Koteska ◽  
...  
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Glucose Level ◽  
Invasive Procedure ◽  
Development Trend ◽  
Glucose Measurement ◽  
Daily Routine ◽  
Network Methods

Diabetes is one of today’s greatest global problems, and it is only becoming bigger. Constant measuring of blood glucose level is a prerequisite for monitoring glucose blood level and establishing diabetes treatment procedures. The usual way of glucose level measuring is by an invasive procedure that requires finger pricking with the lancet and might become painful and obeying, especially if this becomes a daily routine. In this study, we analyze noninvasive glucose measurement approaches and present several classification dimensions according to different criteria: size, invasiveness, analyzed media, sensing properties, applied method, activation type, response delay, measurement duration, and access to results. We set the focus on using machine learning and neural network methods and correlation with heart rate variability and electrocardiogram, as a new research and development trend.

The incidence of stress symptoms and heart rate variability during sleep and orthostatic test

2010 ◽  
Vol 111 (5) ◽  
pp. 733-741 ◽  
Author(s):  
Esa Hynynen ◽  
Niilo Konttinen ◽  
Ulla Kinnunen ◽  
Heikki Kyröläinen ◽  
Heikki Rusko
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Orthostatic Test ◽  
Stress Symptoms
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