scholarly journals Зміни варіабельності серцевого ритму щурів при модуляції аміназином центральної норадренергічної нейротрансмісії протягом тривалого стресу

2012 ◽  
Vol 3 (1) ◽  
pp. 54-61
Author(s):  
O. Z. Мelnikova
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Stress Reaction ◽  
Noradrenergic System ◽  
Spectral Indices ◽  
Great Role ◽  
Alpha Adrenoceptors ◽  
Prolonged Stress ◽  
Central Noradrenergic System ◽  
Research Show

It’s established that under the prolonged stress there were changes of geometric and spectral indices of the rats’ heart rate variability (HRV), manifestations of which depended on duration of stressful factors acting and represented the stress reaction development from the stage of anxiety to the exhaustion phase. Application of chlorpromazine at the beginning and against the background of stress blocked the central alpha adrenoceptors and contributed to renewal of the most HRV indices into the limits of control values at the end of experiment. The results of research show that the modulation of functional state of central noradrenergic system plays a great role in the changes of HRV during prolonged stress. 

Sleep Stage Assessment Using Power Spectral Indices of Heart Rate Variability With a Simple Algorithm

2012 ◽  
Vol 15 (3) ◽  
pp. 264-272 ◽  
Author(s):  
Keiko Tanida ◽  
Masashi Shibata ◽  
Margaret M. Heitkemper
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Sleep Stage ◽  
Sleep Onset ◽  
Low Frequency ◽  
Simple Algorithm ◽  
Sleep Stages ◽  
Spectral Indices ◽  
Current Form ◽  
Power Spectral

Clinical researchers do not typically assess sleep with polysomnography (PSG) but rather with observation. However, methods relying on observation have limited reliability and are not suitable for assessing sleep depth and cycles. The purpose of this methodological study was to compare a sleep analysis method based on power spectral indices of heart rate variability (HRV) data to PSG. PSG and electrocardiography data were collected synchronously from 10 healthy women (ages 20–61 years) over 23 nights in a laboratory setting. HRV was analyzed for each 60-s epoch and calculated at 3 frequency band powers (very low frequency [VLF]-hi: 0.016–0.04 Hz; low frequency [LF]: 0.04–0.15 Hz; and high frequency [HF]: 0.15–0.4 Hz). Using HF/(VLF-hi + LF + HF) value, VLF-hi, and heart rate (HR) as indices, an algorithm to categorize sleep into 3 states (shallow sleep corresponding to Stages 1 & 2, deep sleep corresponding to Stages 3 & 4, and rapid eye movement [REM] sleep) was created. Movement epochs and time of sleep onset and wake-up were determined using VLF-hi and HR. The minute-by-minute agreement rate with the sleep stages as identified by PSG and HRV data ranged from 32 to 72% with an average of 56%. Longer wake after sleep onset (WASO) resulted in lower agreement rates. The mean differences between the 2 methods were 2 min for the time of sleep onset and 6 min for the time of wake-up. These results indicate that distinguishing WASO from shallow sleep segments is difficult using this HRV method. The algorithm's usefulness is thus limited in its current form, and it requires additional modification.

Response to, “The unnormalized spectral indices of heart rate variability should be presented in conjunction with normalized versions of the same variables”

2014 ◽  
Vol 15 (7) ◽  
pp. 843-844 ◽  
Author(s):  
Anna Vlahandonis ◽  
Stephanie R. Yiallourou ◽  
Scott A. Sands ◽  
Gillian M. Nixon ◽  
Margot J. Davey ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Spectral Indices

The unnormalized spectral indices of heart rate variability should be presented in conjunction with normalized versions of the same variables

2014 ◽  
Vol 15 (7) ◽  
pp. 843
Author(s):  
Ertugrul Kurtoglu ◽  
Sevket Balta ◽  
Yasin Karakus ◽  
Erdogan Yasar ◽  
Gokhan Gozubuyuk
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Spectral Indices

Circadian rhythm of spectral indices of heart rate variability in healthy subjects

2005 ◽  
Vol 38 (3) ◽  
pp. 239-243 ◽  
Author(s):  
Andrzej Bilan ◽  
Agnieszka Witczak ◽  
Robert Palusiński ◽  
Wojciech Myśliński ◽  
Janusz Hanzlik
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Circadian Rhythm ◽  
Healthy Subjects ◽  
Spectral Indices

DIABETIC AUTONOMIC NEUROPATHY DETECTION BY HEART-RATE VARIABILITY POWER-SPECTRAL ANALYSIS

2012 ◽  
Vol 12 (03) ◽  
pp. 1250039
Author(s):  
KAMALAKAR DESAI ◽  
DHANJOO N. GHISTA ◽  
ISSAM JAHA EL MUGAMEX ◽  
U. RAJENDRA ACHARYA ◽  
MICHAEL TOWSEY ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Autonomic Neuropathy ◽  
Diabetic Autonomic Neuropathy ◽  
Rate Variation ◽  
Spectral Indices ◽  
Data Set ◽  
Nervous Systems ◽  
Power Spectral ◽  
Non Stationary Signal

Heart rate is a non-stationary signal and provides a powerful interplay between the sympathetic and parasympathetic nervous systems. The heart rate variation signal can reveal disorders associated with how these nervous systems regulate the heart rate, and hence may contain indicators of this disease state, or warnings about impending or future cardiac diseases. These indicators may be present at all times or may occur at random during certain intervals in the time scale. It is difficult and time consuming to pinpoint these abnormalities in a huge cardiac data set. Heart rate variability (HRV) constitutes a tool for assessing the activities of the autonomic nervous system (ANS). In this work, we have proposed a computer based analytical system to determine the HRV, and analyzed it to obtain HRV Power-spectrum for normal, diabetes and diabetes with neuropathy subjects in deep breathing, standing and supine position. We have then designated indices based on the HRV power-spectra power values and frequency shift of these peaks from their normal frequency values. We have shown the efficacy and sensitivity of these indices, to differentiate between normals, diabetics and diabetics with ischemic heart disease. Thus we have demonstrated how effectively these HRV power-spectral indices can enable diagnosis of diabetic autonomic neuropathy. Finally, we have composed an integrated index made up of these power-spectral indices, to facilitate distinguishing and diagnosing diabetic autonomic neuropathy in terms of just one index or number.

scholarly journals INFLUENCE OF ANTIARRHYTHMIC DRUGS ON THE SPECTRAL ANALYSIS OF HEART RATE VARIABILITY IN PATIENTS WITH ATRIAL FIBRILLATION

2018 ◽  
Vol 21 (1-2) ◽  
pp. 101-104
Author(s):  
Ekaterina P. Popova ◽  
O. T Bogova ◽  
S. N Puzin ◽  
I. S Matsokin ◽  
A. A Gadzhimagomedova ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Nervous System ◽  
Spectral Analysis ◽  
Antiarrhythmic Drugs ◽  
Spectral Indices ◽  
Heart Activity ◽  
Class Iii ◽  
Sympathetic Nervous

The use of the spectral analysis of the heart rate variability to assess the effectiveness of therapy is of great attention of researchers and doctors. This method allows you to get knowledge of the influence of the autonomic nervous system on the heart activity, which is an important factor for the manifestation of the effects of antiarrhythmic drugs. In this study, we studied the effect of antiarrhythmic drugs of class III amiodarone and sotalol on spectral indices of the heart rate variability in patients with atrial fibrillation. The power of slow frequencies prevailed in the structure of the spectrum with the introduction of amiodarone and sotalol. This suggests that the sympathetic nervous system have a predominant influence on the heart.

The relationships between heart rate deceleration capacity and spectral indices of heart rate variability during different breathing frequencies

2016 ◽  
Vol 116 (7) ◽  
pp. 1281-1287 ◽  
Author(s):  
Yong-Ping Wang ◽  
Terry B. J. Kuo ◽  
Jia-Yi Li ◽  
Chun-Ting Lai ◽  
Cheryl C. H. Yang
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Spectral Indices ◽  
Heart Rate Deceleration ◽  
Deceleration Capacity ◽  
Rate Deceleration

Circadian variation of spectral indices of heart rate variability after myocardial infarction

1992 ◽  
Vol 123 (6) ◽  
pp. 1521-1529 ◽  
Author(s):  
Federico Lombardi ◽  
Giulia Sandrone ◽  
Andrea Mortara ◽  
Maria Teresa La Rovere ◽  
Ettore Colombo ◽  
...  
Keyword(s):  
Myocardial Infarction ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Circadian Variation ◽  
Spectral Indices

Bias and uncertainty in heart rate variability spectral indices due to the finite ECG sampling frequency

2004 ◽  
Vol 25 (2) ◽  
pp. 489-504 ◽  
Author(s):  
M A García-González ◽  
M Fernández-Chimeno ◽  
J Ramos-Castro
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Sampling Frequency ◽  
Spectral Indices
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