
Causal Relationship Analysis of Heart Rate Variability and Band Power Time Series of Electroencephalographic Signals
Author(s) -
MariNieves Pardo-Rodriguez,
Erik Bojorges-Valdez,
Oscar Yanez-Suarez
Publication year - 2020
Publication title -
2019 computing in cardiology (cinc)
Language(s) - English
Resource type - Conference proceedings
SCImago Journal Rank - 0.257
H-Index - 55
ISSN - 2325-887X
ISBN - 978-1-7281-6936-1
DOI - 10.22489/cinc.2019.131
Subject(s) - bioengineering , computing and processing , signal processing and analysis
This study aimed to find whether there is a causal relationship between band power time series (BP ts ) extracted from EEG and heart rate variability (HRV). Such relationships were explored during spontaneous and a controlled breathing tasks. Data analyzed were recordings obtained from 14 healthy subjects using one ECG lead and 21 EEG channels. The RR intervals from the ECG were used to obtain the HRV signal, which was decomposed with Empirical Mode Decomposition into components of different spectral content known as intrinsic mode functions (IMFs). Granger causality tests were run for the BP ts of alpha, beta and gamma frequency ranges of the EEG signal and the HRV signals IMFs. G-causality increased for three different conditions: slower IMFs (IMF4), BP ts of higher frequency (gamma) band and during task realization. Meaning, gamma’s BP ts G-caused HRV for a larger number of subjects and channels. Also there was a larger incidence on the number of channels that G-caused HRV during the controlled breathing task. The causal influence from the BP ts of EEG signals to the HRV IMFs suggests there is an indirect or unobserved interaction between instantaneous changes on EEG band power and components of HRV which may explain changes in its dynamics.