Tuesday 19th of September 2017
 

A New IPFM Based Model For Artifitial Generating Of HRV With Random Input


Gholamreza Attarodi, Nader Jafarnia Dabanloo, Zahra Abbasvandi and Nazanin Hemmati

The heart rate variability (HRV) signal is a useful and non-invasive tool for the evaluation of cardiovascular system and Autonomic Nervous System. Many researcher tried to model this signal. There are many different approaches for this modelling. One of the most frequently used method is Integral Pulse Frequency Modulator (IPFM) model. In IPFM model there is an input signal which is fed to an integrator and when the output of the integrator reaches to a threshold then we have a pulse. This pulse simulates the R-wave of the ECG signal. The source of ECG is sinoatrial (SA) node. SA node is affected by many factors. The power spectrum of HRV signal is divided into three main bands i.e. VLF, LF and HF. The information in these three bands shows how the Autonomic Nervous System (ANS) affects on heart activity. The ratio LF/HF is related to sampatho-vagal balance. The proposed model generates both normal HRV and HRV of some abnormalities with regard to ANS. As we used random signal in the input of the IPFM the output of the model has random variations and the output never be as a periodic signal. Our model is very similar to real HRV than a normal IPFM. In our previous work we added the random signal to threshold and now we apply the random signal to the main input. We used Guassian random signal with zero mean with variance equals to 1

Keywords: Random Distribution , Heart Rate Variability Signal, Mathematical Model, IPFM Model.

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ABOUT THE AUTHORS

Gholamreza Attarodi
has taught mathematics and modeling in academic courses. He is interested in biomedical modeling, and application of mathematics in biology.

Nader Jafarnia Dabanloo
has taught electronics, mathematics and modeling in academic courses. He is interested in biomedical modeling, signal processing and application of mathematics in biology. He has been dean of Biomedical Engineering Faculty, Science and Research Branch, Islamic Azad University from 2009 to 2011

Zahra Abbasvandi
is student of M.Sc. in Amirkabir University of technology(Tehran polytechnic), she is interested in signal processing and biomedical modeling, and Neural Network.

Nazanin Hemmati
she is interested in image and signal processing and neural network.


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