Nader Jafarnia Dabanloo

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Poincare plot analysis of RR time series allows a beat-to-beat approach to Heart Rate Variability (HRV), detecting patterns associated with nonlinear processes. Since the measurement of standards descriptors of Poincare plot is based on the point's distribution in relation to the line of identity (y=x), we have concentrated on it and evaluated the points(More)
In this paper, a novel method for representation of heart rate has been introduced which is obtaining by using RR interval time series signal to plot the Triangle mapping consist of all the ordered pairs: (RR<inf>i</inf>, abs (RR&#x0305; &#x2013; RR<inf>i</inf>), i = 1, &#x2026;, N where RR&#x0305; is the mean of RR intervals. We obtained a triangle from(More)
The nonlinear analysis of Heart Rate Variability (HRV) is a valuable tool in both clinical practice and physiological research reflecting the ability of the cardiovascular system. Poincare plot is a geometrical representation of RR time series to demonstrate patterns of heart rate dynamics resulting from nonlinear processes. In this paper, by using Poincare(More)
This paper is the follow-up of our previous work presented for CinC/PhysioNet Challenge 2007 on the &#x201C;electrocardiographic imaging of myocardial infarction&#x201D;. We have presented an automatic method for MI location detection by Neural Network classification of BSPM data.
Heart rate variability (HRV) is a very useful signal to investigate the activity of the autonomic nervous system (ANS), which affects and the heart function. Constructing a mathematical model for producing artificial HRV signal is needed to get a conceptual understanding of how ANS controls the heart rate (HR). The integral pulse frequency modulation (IPFM)(More)
Low and high valence were induced in 20 male volunteers using two groups of pictures stimuli. Heart response was compared between two groups from RR series extracted from recorded ECG measurements. Mean heart rate and heart rate variability measures including time, frequency and Poincare domain were extracted. The results revealed that HRV triangular index,(More)
We showed in our recent work that Bidirectional neural network (BNN) is a powerful tool for feature compensation in automatic speech recognition systems. In this paper, we have introduced BNN as feature compensator for better discriminating of pathological voices from normal subjects. Mel-Frequency Cepstral Coefficients (MFCCs) were extracted from each(More)
Recently, heart rate variability (HRV) analysis has been used as an indicator of epileptic seizures. As women have a lower sudden, unexpected death in epilepsy risk and greater longevity than men, the authors postulated that there are significant gender-related differences in heart rate dynamics of epileptic patients. The authors analyzed HRV during(More)
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