发表刊物：IEEE Journal of Biomedical and Health Informatics

项目来源：National Natural Science Foundation of China (Projects 61271380, U1501251, and U1201251), in part

关键字：Average Kendall's tau (AKT), average Pearson’s product moment correlation coefficient (APPMCC), concordance coefficients, kendall's concordance coefficients (KCC), order statistics concordance coefficients (OSCOC), three-way receiver operating characteristic (ROC), volume under the surface (VUS).

摘要：In this paper, we propose a novel concordance coefficient, called order statistics concordance coefficient (OSCOC), to quantify the association among multichannel biosignals. To uncover its properties, we compare OSCOC with three other similar indexes, i.e., average Pearson’s product moment correlation coefficient (APPMCC), Kendall’s concordance coefficients (KCC), and average Kendall’s tau (AKT), under a multivariate normal model (MNM), linear model (LM), and nonlinear model. To further demonstrate its usefulness, we present an example on atrial arrhythmia analysis based on real-world multichannel cardiac signals. Theoretical derivations as well as numerical results suggest that 1) under MNM and LM, OSCOC performs equally well with APPMCC, and outperforms the other two methods, 2) in nonlinear case, OSCOC even has better performance than KCC and AKT, which are well known to be robust under increasing nonlinear transformations, and 3) OSCOC performs the best in the case study of arrhythmia analysis in terms of the volume under the surface.

第一作者：徐维超

论文类型：期刊论文

卷号：21

期号：5

页面范围：1206-1215

是否译文：否

发表时间：2016-10-11

收录刊物：SCI