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

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题名:	Complexity of cardiac signals for predicting changes in alpha-waves after stress in patients undergoing cardiac catheterization
作者:	羅孟宗;Chiu, Hung-Chih;Lin, Yen-Hung;Lo, Men-Tzung;Tang, Sung-Chun;Wang, Tzung-Dau;Lu, Hung-Chun;Ho, Yi-Lwun;Ma, Hsi-Pin;Peng, Chung-Kang
贡献者:	生醫理工學院生醫科學與工程學系
关键词:	639/705/1042;639/705/1046;692/53/2421;Alpha Rhythm - physiology;Cardiac catheterization;Cardiac Catheterization - psychology;Catheterization;Demography;EEG;Electrocardiography;Electroencephalography;Entropy;Female;Fourier analysis;Fourier transforms;Heart - physiopathology;Heart diseases;Heart rate;Humanities and Social Sciences;Humans;Male;Mathematical models;Middle Aged;multidisciplinary;Myocardial Revascularization;Neurotransmitter Agents - blood;Regression Analysis;Science;Signal Processing, Computer-Assisted;Stress, Psychological - blood;Stress, Psychological - physiopathology
日期:	2015-08-19
上传时间:	2026-04-23 11:15:23 (UTC+8)
出版者:	Nature Publishing Group;London: Nature Publishing Group UK
摘要:	摘要： 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. 其他題名： Sci Rep 出版者： London: Nature Publishing Group UK 出版日期： 2015-08-19 出處： Scientific reports, 2015-08, Vol.5 (1), p.13315, Article 13315 資源來源： Publicly Available Content Database 版權： The Author(s) 2015 版權： Copyright Nature Publishing Group Aug 2015 版權： Copyright © 2015, Macmillan Publishers Limited 2015 Macmillan Publishers Limited 識別號： ISSN: 2045-2322 識別號： EISSN: 2045-2322 識別號： DOI: 10.1038/srep13315 識別號： PMID: 26286628
显示于类别:	[生醫科學與工程學系] 期刊論文

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