The continuous reciprocal interplay underlying cerebral and cardiovascular interactions has been shown to generate complex and nonlinear dynamics. To this extent, differences in induced cross-temporal dynamics are here investigated via wavelet-based multivariate multiscale analysis. Twelve features were extracted from both EEG and ECG recordings from 24 healthy subjects at rest and during a cold-pressor test. The proposed multivariate analysis using the eigenstructure of the multiscale decomposition was compared with a classical multivariate analysis. Preliminary results show that differences between experimental conditions are enhanced by the application of the proposed multivariate analysis.

Multiscale Eigen Analysis on EEG and Heartbeat Dynamics: a Pilot study

Abry P.;Barbieri R.
2020-01-01

Abstract

The continuous reciprocal interplay underlying cerebral and cardiovascular interactions has been shown to generate complex and nonlinear dynamics. To this extent, differences in induced cross-temporal dynamics are here investigated via wavelet-based multivariate multiscale analysis. Twelve features were extracted from both EEG and ECG recordings from 24 healthy subjects at rest and during a cold-pressor test. The proposed multivariate analysis using the eigenstructure of the multiscale decomposition was compared with a classical multivariate analysis. Preliminary results show that differences between experimental conditions are enhanced by the application of the proposed multivariate analysis.
2020
2020 11th Conference of the European Study Group on Cardiovascular Oscillations: Computation and Modelling in Physiology: New Challenges and Opportunities, ESGCO 2020
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1170291
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