| Summary: | 碩士 === 長庚大學 === 電子工程學系 === 103 === The purpose of this study is to develop a novel index that combined heart rate variability (HRV) and nonlinear analysis, and used to measure cardiac stress. During physical exercise, the index can reflect the status of cardiac stress. In the experiment, we obtained the RR time series with electrocardiogram (ECG) data by the subjects undergoing cycling exercise, thereby estimated heart rate (HR), standard deviation, spectral measure of HRV as well as a nonlinear detrended fluctuation analysis (DFA).There are eleven young healthy subjects were recruited in our test.And each of the subjects was required to under a certain load and maintained a fixed speed during pedaling test.HR, Standard deviation of the normal-to-normal interval (SDNN), the high-fidelity power spectral density (PSD) of HRV, and the DFA scaling exponent α were estimated by test.And then do analysis of variance (ANOVA) and multivariate linear regression analysis.As a result, HR would increase, both SDNN and α would decrease, and lower frequency to higher frequency (LF-to-HF) spectral power ratio of HRV was no significant correlation during cycling exercise.This mean HR,SDNN and α may further detect the heart stress status during physical exercise.We further use linear discriminant analysis (LDA) for these three features to make the task of cardiac stress stratification.Finally, we obtained a time-varying parameter and can be used for on-line measurement of cardiac stress status index, called cardiac stress measure(CSM).
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