scholarly journals Performance Comparison of Time-Frequency Distributions for Estimation of Instantaneous Frequency of Heart Rate Variability Signals

2017 ◽  
Vol 7 (3) ◽  
pp. 221 ◽  
Author(s):  
Nabeel Khan ◽  
Peter Jönsson ◽  
Maria Sandsten
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Instantaneous Frequency ◽  
Performance Comparison ◽  
Frequency Distributions ◽  
Time Frequency

scholarly journals Nonlinearities of heart rate variability in animal models of impaired cardiac control: contribution of different time scales

2017 ◽  
Vol 123 (2) ◽  
pp. 344-351 ◽  
Author(s):  
Luiz Eduardo Virgilio Silva ◽  
Renata Maria Lataro ◽  
Jaci Airton Castania ◽  
Carlos Alberto Aguiar Silva ◽  
Helio Cesar Salgado ◽  
...  
Keyword(s):  
Nonlinear Dynamics ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Time Scales ◽  
Multiscale Entropy ◽  
Time Frequency ◽  
Cardiac Control ◽  
Long Time ◽  
Nonlinear Features ◽  
Short Time

Heart rate variability (HRV) has been extensively explored by traditional linear approaches (e.g., spectral analysis); however, several studies have pointed to the presence of nonlinear features in HRV, suggesting that linear tools might fail to account for the complexity of the HRV dynamics. Even though the prevalent notion is that HRV is nonlinear, the actual presence of nonlinear features is rarely verified. In this study, the presence of nonlinear dynamics was checked as a function of time scales in three experimental models of rats with different impairment of the cardiac control: namely, rats with heart failure (HF), spontaneously hypertensive rats (SHRs), and sinoaortic denervated (SAD) rats. Multiscale entropy (MSE) and refined MSE (RMSE) were chosen as the discriminating statistic for the surrogate test utilized to detect nonlinearity. Nonlinear dynamics is less present in HF animals at both short and long time scales compared with controls. A similar finding was found in SHR only at short time scales. SAD increased the presence of nonlinear dynamics exclusively at short time scales. Those findings suggest that a working baroreflex contributes to linearize HRV and to reduce the likelihood to observe nonlinear components of the cardiac control at short time scales. In addition, an increased sympathetic modulation seems to be a source of nonlinear dynamics at long time scales. Testing nonlinear dynamics as a function of the time scales can provide a characterization of the cardiac control complementary to more traditional markers in time, frequency, and information domains. NEW & NOTEWORTHY Although heart rate variability (HRV) dynamics is widely assumed to be nonlinear, nonlinearity tests are rarely used to check this hypothesis. By adopting multiscale entropy (MSE) and refined MSE (RMSE) as the discriminating statistic for the nonlinearity test, we show that nonlinear dynamics varies with time scale and the type of cardiac dysfunction. Moreover, as complexity metrics and nonlinearities provide complementary information, we strongly recommend using the test for nonlinearity as an additional index to characterize HRV.

Heart Rate Variability Assessment and Its Application for Autonomic Function Evaluation in Patients with Hyperhidrosis

2020 ◽  
Vol 83 (3) ◽  
pp. 293-300
Author(s):  
Aracy Satoe Mautari Niwa ◽  
Michele Lima Gregório ◽  
Luiz Eduardo Villaça Leão ◽  
Moacir Fernandes de Godoy
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Nervous System ◽  
Point Of View ◽  
Function Evaluation ◽  
Recurrence Plots ◽  
Time Frequency ◽  
Hrv Analysis ◽  
Focal Hyperhidrosis ◽  
Systemic Component

Background: Pathophysiology mechanism of primary focal hyperhidrosis (PFHH) is controversial. Heart rate variability (HRV) could explain if there is a systemic component present. We aimed to investigate the functions of the autonomic nervous system in patients diagnosed with PFHH compared to controls using the analysis of HRV in the domains of time, frequency, and nonlinearity, as well as analysis of the recurrence plots (RPs). Methods: We selected 34 patients with PFHH (29.4 ± 10.2 years) and 34 controls (29.2 ± 9.6 years) for HRV analysis. Heart beats were recorded with Polar RS800CX monitor (20 min, at rest, in supine position), and RR intervals were analyzed with Kubios Premium HRV software. RPs were constructed with Visual Recurrence Analysis software. Statistical analysis included unpaired t test (p < 0.05). Results: Our results showed that HRV parameters in the 3 domains evaluated did not show any differences between the groups. The same was observed with RPs. Conclusions: The findings suggest that PFHH, from the pathophysiological point of view, may be caused by peripheral involvement of the sympathetic nervous system (glandular level or nerve terminals), as there was no difference between the groups studied. More specific studies should help elucidate this issue.

Time-frequency analysis of heart rate variability using short-time Fourier analysis

2000 ◽  
Vol 21 (2) ◽  
pp. 229-240 ◽  
Author(s):  
Sigrid Elsenbruch ◽  
Zhishun Wang ◽  
William C Orr ◽  
J D Z Chen
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Fourier Analysis ◽  
Frequency Analysis ◽  
Time Frequency Analysis ◽  
Time Frequency ◽  
Short Time
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