Complexity of cardiac signals for predicting changes in alpha-waves after stress in patients undergoing cardiac catheterization.
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 quantify the power of EEG. The clinical, HRV, and EEG parameters of postcatheterization EEG alpha waves were analyzed using change-score analysis and generalized additive models. In conclusion, the complexity of cardiac electrical signals can be used to predict EEG changes after stress.
Department of Electrical Engineering, National Tsing Hua University, Hsinchu, Taiwan.
Hung-Chih
HC
Chiu
Department of Internal Medicine, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei, Taiwan.
Yen-Hung
YH
Lin
1] Institute of Translational and Interdisciplinary Medicine and Department of Biomedical Sciences and Engineering, National Central University, Chungli, Taiwan [2] Research Center for Adaptive Data Analysis, National Central University, Taoyuan, Taiwan.
Men-Tzung
MT
Lo
Department of Neurology, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei, Taiwan.
Sung-Chun
SC
Tang
Department of Internal Medicine, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei, Taiwan.
Tzung-Dau
TD
Wang
Department of Internal Medicine, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei, Taiwan.
Hung-Chun
HC
Lu
Department of Internal Medicine, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei, Taiwan.
Yi-Lwun
YL
Ho
Department of Electrical Engineering, National Tsing Hua University, Hsinchu, Taiwan.
Hsi-Pin
HP
Ma
1] Research Center for Adaptive Data Analysis, National Central University, Taoyuan, Taiwan [2] Division of Interdisciplinary Medicine and Biotechnology, Beth Israel Deaconess Medical Center/Harvard Medical School, Boston, Massachusetts, USA.
Chung-Kang
CK
Peng
D000513:Alpha Rhythm / Q000502:physiology*; D006328:Cardiac Catheterization / Q000523:psychology*; D003710:Demography; D004562:Electrocardiography; D004569:Electroencephalography; D005260:Female; D006321:Heart / Q000503:physiopathology*; D006801:Humans; D008297:Male; D008875:Middle Aged; D009204:Myocardial Revascularization; D018377:Neurotransmitter Agents / Q000097:blood; D012044:Regression Analysis; D012815:Signal Processing, Computer-Assisted; D013315:Stress, Psychological / Q000097:blood / Q000503:physiopathology*
D018377:Neurotransmitter Agents