Spectral Analysis of Heart Rate Variability as a Quantitative Measure of Parasympatholytic Effect-Integrated Pharmacokinetics and Pharmacodynamics of Three Anticholinergic Drugs

1999 ◽  
Vol 21 (2) ◽  
pp. 141-151 ◽  
Author(s):  
Harry Scheinin ◽  
Antti Helminen ◽  
Sakke Huhtala ◽  
Paula Grönroos ◽  
Job A. Bosch ◽  
...  
1996 ◽  
Vol 27 (2) ◽  
pp. 398-399
Author(s):  
Tohru Kaji ◽  
Tetsuro Kohya ◽  
Fumishi Tomita ◽  
Tomohide Ono ◽  
Akira Kitabatake

2005 ◽  
Vol 288 (1) ◽  
pp. H424-H435 ◽  
Author(s):  
Riccardo Barbieri ◽  
Eric C. Matten ◽  
AbdulRasheed A. Alabi ◽  
Emery N. Brown

Heart rate is a vital sign, whereas heart rate variability is an important quantitative measure of cardiovascular regulation by the autonomic nervous system. Although the design of algorithms to compute heart rate and assess heart rate variability is an active area of research, none of the approaches considers the natural point-process structure of human heartbeats, and none gives instantaneous estimates of heart rate variability. We model the stochastic structure of heartbeat intervals as a history-dependent inverse Gaussian process and derive from it an explicit probability density that gives new definitions of heart rate and heart rate variability: instantaneous R-R interval and heart rate standard deviations. We estimate the time-varying parameters of the inverse Gaussian model by local maximum likelihood and assess model goodness-of-fit by Kolmogorov-Smirnov tests based on the time-rescaling theorem. We illustrate our new definitions in an analysis of human heartbeat intervals from 10 healthy subjects undergoing a tilt-table experiment. Although several studies have identified deterministic, nonlinear dynamical features in human heartbeat intervals, our analysis shows that a highly accurate description of these series at rest and in extreme physiological conditions may be given by an elementary, physiologically based, stochastic model.


2002 ◽  
Author(s):  
Zengyong Li ◽  
Kun Jiao ◽  
Ming Chen ◽  
Yushu Yang ◽  
Chengtao Wang ◽  
...  

2005 ◽  
Vol 289 (4) ◽  
pp. H1729-H1735 ◽  
Author(s):  
Sophie Motte ◽  
Myrielle Mathieu ◽  
Serge Brimioulle ◽  
Anne Pensis ◽  
Lynn Ray ◽  
...  

Heart failure is associated with autonomic imbalance, and this can be evaluated by a spectral analysis of heart rate variability. However, the time course of low-frequency (LF) and high-frequency (HF) heart rate variability changes, and their functional correlates during progression of the disease are not exactly known. Progressive heart failure was induced in 16 beagle dogs over a 7-wk period by rapid ventricular pacing. Spectral analysis of heart rate variability and respiration, echocardiography, hemodynamic measurements, plasma atrial natriuretic factor, and norepinephrine was obtained at baseline and every week, 30 min after pacing interruption. Progressive heart failure increased heart rate (from 91 ± 4 to 136 ± 5 beats/min; P < 0.001) and decreased absolute and normalized (percentage of total power) HF variability from week 1 and 2, respectively ( P < 0.01). Absolute LF variability did not change during the study until it disappeared in two dogs at week 7 ( P < 0.05). Normalized LF variability increased in moderate heart failure ( P < 0.01), leading to an increased LF-to-HF ratio ( P < 0.05), but decreased in severe heart failure ( P < 0.044; week 7 vs. week 5). Stepwise regression analysis revealed that among heart rate variables, absolute HF variability was closely associated with wedge pressure, right atrial and pulmonary arterial pressure, left ventricular ejection fraction and volume, ratio of maximal velocity of early (E) and atrial (A) mitral flow waves, left atrial diameter, plasma norepinephrine, and atrial natriuretic peptide (0.45 < r < 0.65, all P < 0.001). In tachycardia-induced heart failure, absolute HF heart rate variability is a more reliable indicator of cardiac dysfunction and neurohumoral activation than LF heart rate variability.


2001 ◽  
Vol 62 (1) ◽  
pp. 37-42 ◽  
Author(s):  
Toshiyuki Matsunaga ◽  
Takuma Harada ◽  
Takeshi Mitsui ◽  
Masanori Inokuma ◽  
Masatoshi Hashimoto ◽  
...  

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