期刊
MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING
卷 44, 期 4, 页码 321-330出版社
SPRINGER HEIDELBERG
DOI: 10.1007/s11517-006-0038-0
关键词
nonlinear regression; heart rate variability; modeling; time series analysis
In this contribution we test the hypothesis that nonlinear additive autoregressive model-based data analysis improves the diagnostic ability based on short-term heart rate variability. For this purpose, a nonlinear regression approach, namely, the maximal correlation method is applied to the data of 37 patients with dilated cardiomyopathy as well as of 37 age- and sex-matched healthy subjects. We find that this approach is a powerful tool in discriminating both groups and promising for further model-based analyses.
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