A new Frequency Domain Measure of Causality based on Partial Spectral Decomposition of Autoregressive Processes and its Application to Cardiovascular Interactions

Riccardo Pernice, Luca Faes, Alessandro Busacca, Jana Krohova, Michal Javorka

Risultato della ricerca: Conference contribution

4 Citazioni (Scopus)

Abstract

We present a new method to quantify in the frequency domain the strength of directed interactions between linear stochastic processes. This issue is traditionally addressed by the directed coherence (DC), a popular causality measure derived from the spectral representation of vector autoregressive (AR) processes. Here, to overcome intrinsic limitations of the DC when it needs to be objectively quantified within specific frequency bands, we propose an approach based on spectral decomposition, which allows to isolate oscillatory components related to the pole representation of the vector AR process in the Z-domain. Relating the causal and non-causal power content of these components we obtain a new spectral causality measure, denoted as pole-specific spectral causality (PSSC). In this study, PSSC is compared with DC in the context of cardiovascular variability analysis, where evaluation of the spectral causality from arterial pressure to heart period variability is of interest to assess baroreflex modulation in the low frequency band (0.04-0-15 Hz). Using both a theoretical example in which baroreflex interactions are simulated, and real cardiovascular variability series measured from a group of healthy subjects during a postural challenge, we show that – compared with DC– PSSC leads to a frequency-specific evaluation of spectral causality which is more objective and more focused on the frequency band of interest.
Lingua originaleEnglish
Titolo della pubblicazione ospite2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Pagine4258-4261
Numero di pagine4
Stato di pubblicazionePublished - 2019

Serie di pubblicazioni

NomeIEEE ENGINEERING IN MEDICINE AND BIOLOGY ... ANNUAL CONFERENCE PROCEEDINGS

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

Fingerprint Entra nei temi di ricerca di 'A new Frequency Domain Measure of Causality based on Partial Spectral Decomposition of Autoregressive Processes and its Application to Cardiovascular Interactions'. Insieme formano una fingerprint unica.

Cita questo