Self-similar properties of long term heart rate variability assessed by discrete wavelet transform

Censi, Federica; Cesarini, A; Lino, S.; Cerutti, Alberto

doi:10.1109/cic.1998.731801

Cited by 2 publications

(3 citation statements)

References 7 publications

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“…The exponent α is calculated by a first leastsquares fit in a log-log spectrum, after finding the power spectrum from RRIs. The exponent α is clinically significant because it has different values for healthy and heart rate failure patients (Calcagnini et al 1998;Signorini et al 1998). …”

Section: Frequency Domain Analysismentioning

confidence: 99%

Coronary artery disease prediction method using linear and nonlinear feature of heart rate variability in three recumbent postures

et al. 2009

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In present study, we proposed not only a novel methodology useful in developing the various features of heart rate variability (HRV), but also a suitable prediction model to enhance the reliability of medical examinations and treatments for coronary artery disease. In order to develop the various features of HRV, we analyzed HRV for three recumbent postures. The interaction effects between the recumbent postures and groups of normal people and heart patients were observed based on linear and nonlinear features of HRV. Forty-three control subjects and 64 patients with coronary artery disease participated in this study. In order to extract various features, we tested five classification methods and evaluated performance of classifiers. As a result, SVM and CMAR (gave about 72-88% goodness of accuracy) outperformed the other classifiers.

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Section: Frequency Domain Analysismentioning

confidence: 99%

Coronary artery disease prediction method using linear and nonlinear feature of heart rate variability in three recumbent postures

et al. 2009

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“…Thus, fractal signals usually have a power spectrum of the inverse power law form, 1/f α , where f is frequency, since the amplitude of the fluctuations is small at high frequencies and large at low frequencies. The exponent α is clinically significant because it has different values for healthy and heart rate failure patients (Signorini et al 1998, Calcagnini et al 1998. After finding the power spectrum from an RR interval time series, the exponent α is calculated by a first least-squares fit in a log-log spectrum (figure 2).…”

Section: Sample Entropy (Sampen) Versus Approximate Entropy (Apen)mentioning

confidence: 99%

“…The α exponent reflects the self-similarity of the signal. It is well known that a normal HRV time series exhibits 1/f α type spectral behaviors in the frequency range between 10 −4 and 10 −2 Hz, and the exponent α is clinically significant because it has different values for healthy and heart rate failure patients (Signorini et al 1998, Calcagnini et al 1998. The decrease in the α exponent from the right lateral decubitus position could be due to an increased irregularity.…”

Section: Nonlinear Measurementioning

confidence: 99%

Nonlinear characteristics of heart rate time series: influence of three recumbent positions in patients with mild or severe coronary artery disease

et al. 2005

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The aim of this study was to investigate the nonlinear characteristics of heart rate variability (HRV) for three recumbent positions: the supine, left lateral and right lateral decubitus positions. Recently, using a linear analyses method (for time and frequency domains), the effect of the right lateral decubitus position on vagal modulation has been found to increase parasympathetic activity and decrease sympathetic modulation. Little is known about the nonlinear dynamics of HRV for the three recumbent positions. Therefore, we studied the correlation dimension (CD), the largest Lyapunov exponent (LLE), the sample entropy (SampEn), the approximate entropy (ApEn) and the exponent alpha of the 1/falpha power spectrum as nonlinear characteristics of HRV. In response to the right lateral decubitus position, the CD, LLE, SampEn and ApEn increased significantly in both coronary artery disease (CAD) and control groups. In the linear analyses, the normalized high-frequency power (nHF) increased in the right lateral decubitus position. The CD, LLE, ApEn and SampEn correlated positively to the nHF. The alpha exponent did not correlate to either linear measure or CD, but correlated negatively to LLE, ApEn and SampEn. Among the three recumbent positions, it was found that the right lateral decubitus position can increase the complexity of the human physiological system and the vagal modulation of the cardiac autonomic nervous system the most.

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Self-similar properties of long term heart rate variability assessed by discrete wavelet transform

Cited by 2 publications

References 7 publications

Coronary artery disease prediction method using linear and nonlinear feature of heart rate variability in three recumbent postures

Coronary artery disease prediction method using linear and nonlinear feature of heart rate variability in three recumbent postures

Nonlinear characteristics of heart rate time series: influence of three recumbent positions in patients with mild or severe coronary artery disease

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