scholarly journals ANALYSIS OF HEART RATE VARIABILITY UNDER COGNITIVE LOAD IN CONDITIONALLY HEALTHY INDIVIDUALS

Author(s):  
Elena Archibasova ◽  
Vyacheslav Kulikov ◽  
Lyudmila Antropova
PLoS ONE ◽  
2019 ◽  
Vol 14 (5) ◽  
pp. e0216731
Author(s):  
Gert Pfurtscheller ◽  
Andreas Schwerdtfeger ◽  
David Fink ◽  
Clemens Brunner ◽  
Christoph Stefan Aigner ◽  
...  

Author(s):  
Renato Paceli ◽  
Aretusa Cardoso ◽  
Matheus Cavalcanti de Sá ◽  
Mauro Walter Vaisberg ◽  
Naomi Kondo Nakagama ◽  
...  

1999 ◽  
Vol 31 (Supplement) ◽  
pp. S251
Author(s):  
R. D. Prisby ◽  
M. A. Alomari ◽  
M. A. Welsch ◽  
R. W. Wood

2018 ◽  
Vol 11 (3) ◽  
pp. 78-93
Author(s):  
I.G. Bodrov ◽  
A.Yu. Shishelova

While analyzing heart rate variability there were detected two types of visceral adaptation to cognitive activities: the first one is characterized by decrease of tension index (Baevskiy, 1984) and increase of heart rate variability at a cognitive load, along with increased power of regulatory effects on the heart rate; the second one is defined by higher heart rate variability, higher power of regulatory effects before the cognitive load and increase of the strain index during cognitive load in the absence of other significant changes. It is peculiar for people related to these types to possess different correlation relationships between the indices of sensory-motor reactions and heart rate variability.


2019 ◽  
Vol 7 ◽  
pp. 870-874
Author(s):  
Galya Nikolova Georgieva-Tsaneva

The paper presents frequency methods for estimating the variability of intervals between individual heart beats in Electrocardiogram. This parameter is known in the scientific literature as the Heart Rate Variability and with this method it is possible to make predictions about human health. Three frequency ranges have been studied: Very Low Frequency, Low Frequency, and High Frequency. The study in this paper was based on real cardiological data obtained from 33 patients suffering from heart fibrillations and 29 healthy individuals. The investigated records are obtained through a Holter monitoring of studied individuals in real life conditions. The obtained results show significantly lower values ​​of the tested spectral parameters in the diseased individuals compared to the healthy controls. The accomplished study shows the effective applicability of the spectral methods of Heart Rate Variability analysis and the possibility of differentiation by the spectral parameters of the patients from healthy individuals.


2020 ◽  
Author(s):  
Valentina Arnao ◽  
Antonio Cinturino ◽  
Sergio Mastrilli ◽  
Carmelo Buttà ◽  
Carlo Maida ◽  
...  

Abstract Background Heart rate variability (HRV) decreases in Parkinson’s disease (PD) and it can be considered a marker for cardiovascular dysautonomia. Purpose To evaluate long-term time-domain analysis of HRV of PD patients and compare the results with those of matched healthy individuals. Method 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-hour 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 score was 10.1±7.3. Patients were on Hoehn & Yahr stage 1-2 and mean Levodopa Equivalent Dose (LED) was 311 ± 239.9. Mean of the 5-minute standard deviation (SD) of R-R intervals distribution (SDNN) for all 5 min segments of the entire recording (ISDNN) was significantly lower in patients compared to controls. ISDNN was significantly different between Parkinson’s disease patients and healthy controls.Conclusion In our population characterized by mild to moderate disease severity, time-domain assessment of HRV seemed to be a potential tool to characterize cardiovascular dysautonomia. Decrease of ISDNN in PD may reflect an autonomic derangement extending all day and night long.


2020 ◽  
Author(s):  
Valentina Arnao ◽  
Antonio Cinturino ◽  
Sergio Mastrilli ◽  
Carmelo Buttà ◽  
Carlo Maida ◽  
...  

Abstract Background Heart rate variability (HRV) decreases in Parkinson’s disease (PD) and it can be considered a marker for cardiovascular dysautonomia. Purpose To evaluate long-term time-domain analysis of HRV of PD patients and compare the results with those of matched healthy individuals. Method 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-hour 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 score was 10.1±7.3. Patients were on Hoehn & Yahr stage 1-2 and mean Levodopa Equivalent Dose (LED) was 311 ± 239.9. Mean of the 5-minute standard deviation (SD) of R-R intervals distribution (SDNN) for all 5 min segments of the entire recording (ISDNN) was significantly lower in patients compared to controls. ISDNN was significantly different between Parkinson’s disease patients and healthy controls. Conclusion In our population characterized by mild to moderate disease severity, time-domain assessment of HRV seemed to be a potential tool to characterize cardiovascular dysautonomia. Decrease of ISDNN in PD may reflect an autonomic derangement extending all day and night long.


PLoS ONE ◽  
2018 ◽  
Vol 13 (11) ◽  
pp. e0206675 ◽  
Author(s):  
Gert Pfurtscheller ◽  
Andreas Schwerdtfeger ◽  
David Fink ◽  
Clemens Brunner ◽  
Christoph Stefan Aigner ◽  
...  

1997 ◽  
Vol 273 (4) ◽  
pp. H1841-H1847 ◽  
Author(s):  
A. Colosimo ◽  
A. Giuliani ◽  
A. M. Mancini ◽  
G. Piccirillo ◽  
V. Marigliano

A data set of R-R intervals recorded for at least 15 min in 141 healthy individuals of different ages and under two different conditions (“resting” and “tilted” states) has been considered. The data have been subjected to spectral analysis by fast Fourier transform methods and considered in view of the possibility to work out a model in which the chronological and cardiac age could be compared. Understanding the results was greatly facilitated by 1) working out a number of derived variables from the original ones to highlight the presence of small but conceptually important variability factors; 2) extraction of the principal components from the original as well as from the derived variables to exclude redundancies and correlation effects; and 3) automatic clustering of the subjects in age classes, which allowed removal of individual variability within each class. The main conclusion is that, within the examined individuals, cardiac and chronological ages do not match for ages higher than ∼50 years; this could reflect the presence of subtle (and difficult-to-envisage) biases in the data analysis or a real discrepancy. The latter hypothesis should be confirmed by similar observations in different systemic contexts. The use of a simple equation relating chronological and cardiac age, derived from a careful regression analysis on our data set and of general use for screening purposes, is demonstrated.


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