scholarly journals Integral pulse frequency modulation model driven by sympathovagal dynamics: Synthetic vs. real heart rate variability

2021 ◽  
Vol 68 ◽  
pp. 102736
Author(s):  
Diego Candia-Rivera ◽  
Vincenzo Catrambone ◽  
Riccardo Barbieri ◽  
Gaetano Valenza
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Frequency Modulation ◽  
Pulse Frequency ◽  
Pulse Frequency Modulation ◽  
Model Driven ◽  
Modulation Model

The Computation of Evoked Heart Rate and Blood Pressure

1999 ◽  
Vol 13 (2) ◽  
pp. 83-91 ◽  
Author(s):  
Greetje Koers ◽  
Lambertus J. M. Mulder ◽  
Frederik M. van der Veen
Keyword(s):  
Blood Pressure ◽  
Heart Rate ◽  
Interpolation Method ◽  
Linear Interpolation ◽  
Pulse Frequency ◽  
Weighted Averaging ◽  
Pulse Frequency Modulation ◽  
Filtering Method ◽  
Blood Pressure Data ◽  
Modulation Model

Abstract For many years psychophysiologists have been interested in stimulus related changes in heart rate and blood pressure. To represent these evoked heart rate and blood pressure patterns, heart rate and blood pressure data have to be transformed into equidistant time series. This paper presents an extensive comparison between two methods. The most often used method is based on linear interpolation, also known as weighted averaging. The low pass filtering method presented here is based on a well-known model for the generation of heart beats, the integral pulse frequency modulation model (IPFM). The comparison shows that the results of the filtering and interpolation procedures are virtually identical. Practically, small differences between the methods disappear in the averaging process. Therefore, the interpolation method is a suitable practical alternative to the computationally complex filtering method.

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