Complexity of cardiac signals for predicting changes in alpha-waves after stress in patients undergoing cardiac catheterization.

ABSTRACT: The hierarchical interaction between electrical signals of the brain and heart is not fully understood. We hypothesized that the complexity of cardiac electrical activity can be used to predict changes in encephalic electricity after stress. Most methods for analyzing the interaction between the heart rate variability (HRV) and electroencephalography (EEG) require a computation-intensive mathematical model. To overcome these limitations and increase the predictive accuracy of human relaxing states, we developed a method to test our hypothesis. In addition to routine linear analysis, multiscale entropy and detrended fluctuation analysis of the HRV were used to quantify nonstationary and nonlinear dynamic changes in the heart rate time series. Short-time Fourier transform was applied to quan

SUBMITTER: Chiu HC 

PROVIDER: S-EPMC4541158 | biostudies-literature | 2015 Aug

REPOSITORIES: biostudies-literature