A robust approach for ECG-based analysis of cardiopulmonary coupling.
Deriving respiratory signal from a surface electrocardiogram (ECG) measurement has advantage of simultaneously monitoring of cardiac and respiratory activities. ECG-based cardiopulmonary coupling (CPC) analysis estimated by heart period variability and ECG-derived respiration (EDR) shows promising applications in medical field. The aim of this paper is to provide a quantitative analysis of the ECG-based CPC, and further improve its performance. Two conventional strategies were tested to obtain EDR signal: R-S wave amplitude and area of the QRS complex. An adaptive filter was utilized to extract the common component of inter-beat interval (RRI) and EDR, generating enhanced versions of EDR signal. CPC is assessed through probing the nonlinear phase interactions between RRI series and respiratory signal. Respiratory oscillations presented in both RRI series and respiratory signals were extracted by ensemble empirical mode decomposition for coupling analysis via phase synchronization index. The results demonstrated that CPC estimated from conventional EDR series exhibits constant and proportional biases, while that estimated from enhanced EDR series is more reliable. Adaptive filtering can improve the accuracy of the ECG-based CPC estimation significantly and achieve robust CPC analysis. The improved ECG-based CPC estimation may provide additional prognostic information for both sleep medicine and autonomic function analysis.
The Quartermaster Research Institute of the General Logistic Department, Beijing, PR China.
Jiewen
J
Zheng
Department of Biomedical Engineering, Chinese PLA (People's Liberation Army) General Hospital, Beijing, PR China.
Weidong
W
Wang
Department of Biomedical Engineering, Chinese PLA (People's Liberation Army) General Hospital, Beijing, PR China; Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA. Electronic address: zhengbozhang@126.com.
Zhengbo
Z
Zhang
Department of Computer Science and Engineering, The University of Tennessee at Chattanooga, Chattanooga, TN 37403, USA.
Dalei
D
Wu
Department of Biomedical Engineering, Chinese PLA (People's Liberation Army) General Hospital, Beijing, PR China.
Hao
H
Wu
Center for Dynamical Biomarkers and Translational Medicine, National Central University, Chungli, Taiwan; Division of Interdisciplinary Medicine & Biotechnology and Margret & H.A. Rey Institute for Nonlinear Dynamics in Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02215, USA.
Chung-Kang
CK
Peng
D002320:Cardiovascular Physiological Phenomena; D004562:Electrocardiography; D012143:Respiratory Physiological Phenomena; D012815:Signal Processing, Computer-Assisted
Adaptive filtering; Cardiopulmonary coupling; ECG-derived respiration; Ensemble empirical mode decomposition; Phase synchronization