@article{TopcuFruehwirthMoseretal.2018,
  author    = {Top{\c{c}}u, {\c{C}}ağda{\c{s}} and Fr{\"u}hwirth, Matthias and Moser, Maximilian and Rosenblum, Michael and Pikovskij, Arkadij},
  title     = {Disentangling respiratory sinus arrhythmia in heart rate variability records},
  series = {Physiological Measurement},
  volume    = {39},
  journal   = {Physiological Measurement},
  number    = {5},
  publisher = {IOP Publ. Ltd.},
  address   = {Bristol},
  issn      = {0967-3334},
  doi       = {10.1088/1361-6579/aabea4},
  pages     = {12},
  year      = {2018},
  abstract  = {Objective: Several different measures of heart rate variability, and particularly of respiratory sinus arrhythmia, are widely used in research and clinical applications. For many purposes it is important to know which features of heart rate variability are directly related to respiration and which are caused by other aspects of cardiac dynamics. Approach: Inspired by ideas from the theory of coupled oscillators, we use simultaneous measurements of respiratory and cardiac activity to perform a nonlinear disentanglement of the heart rate variability into the respiratory-related component and the rest. Main results: The theoretical consideration is illustrated by the analysis of 25 data sets from healthy subjects. In all cases we show how the disentanglement is manifested in the different measures of heart rate variability. Significance: The suggested technique can be exploited as a universal preprocessing tool, both for the analysis of respiratory influence on the heart rate and in cases when effects of other factors on the heart rate variability are in focus.},
  language  = {en}
}
@article{RosenblumFruehwirthMoseretal.2019,
  author    = {Rosenblum, Michael and Fr{\"u}hwirth, Martha and Moser, Maximilian and Pikovskij, Arkadij},
  title     = {Dynamical disentanglement in an analysis of oscillatory systems: an application to respiratory sinus arrhythmia},
  series = {Philosophical Transactions of the Royal Society of London, Series A : Mathematical, Physical and Engineering Sciences},
  volume    = {377},
  journal   = {Philosophical Transactions of the Royal Society of London, Series A : Mathematical, Physical and Engineering Sciences},
  number    = {2160},
  publisher = {Royal Society},
  address   = {London},
  issn      = {1364-503X},
  doi       = {10.1098/rsta.2019.0045},
  pages     = {14},
  year      = {2019},
  abstract  = {We develop a technique for the multivariate data analysis of perturbed self-sustained oscillators. The approach is based on the reconstruction of the phase dynamics model from observations and on a subsequent exploration of this model. For the system, driven by several inputs, we suggest a dynamical disentanglement procedure, allowing us to reconstruct the variability of the system's output that is due to a particular observed input, or, alternatively, to reconstruct the variability which is caused by all the inputs except for the observed one. We focus on the application of the method to the vagal component of the heart rate variability caused by a respiratory influence. We develop an algorithm that extracts purely respiratory-related variability, using a respiratory trace and times of R-peaks in the electrocardiogram. The algorithm can be applied to other systems where the observed bivariate data can be represented as a point process and a slow continuous signal, e.g. for the analysis of neuronal spiking. This article is part of the theme issue 'Coupling functions: dynamical interaction mechanisms in the physical, biological and social sciences'.},
  language  = {en}
}