The Novel Indices of Short-Time Heart Rate Variability for Prediction of Cardiovascular and Cerebrovascular Events | |
Shao SL(邵士亮)(1,2,3); Wang T(王挺)1,2; Song CH(宋纯贺)1,2; Su Y(苏贇)1,2; Zhao H(赵海)3 | |
刊名 | Journal of Medical Imaging and Health Informatics
![]() |
2020 | |
卷号 | 10期号:3页码:769-774 |
关键词 | Heart Rate Variability (HRV) Hilbert Transform Bubble Entropy (BE) Singular Value Decompose (SVD) |
ISSN号 | 2156-7018 |
产权排序 | 1 |
英文摘要 | In this paper, eight novel instantaneous indices of short-time heart rate variability (HRV) signals are proposed for prediction of cardiovascular and cerebrovascular events. The indices are based on Bubble Entropy (BE) and Singular Value Decompose (SVD). The process of indices calculation is as follows, firstly, the instantaneous amplitude (IA), instantaneous frequency (IF) and instantaneous phase (IP) of HRV signals are estimated by the Hilbert transform. Secondly, according to the HRV, IA, IP and IF, the BE and singular value (SV) is calculated, then eight novel indices are obtained, they are BEHRV, BEIA, BEIF, BEIP, SVHRV, SVIA, SVIF and SVIP. Last but not least, in order to evaluate the performance of the eight novel indices for prediction of cardiovascular and cerebrovascular events, the difference analysis of eight indices is carried out by t-test. According to the p value, seven of the eight indices BEHRV, BEIA, BEIF, BEIP, SVIA, SVIF and SVIP are thought to be the indices to discriminate the E group and N group. The K-nearest neighbor (KNN), support vector machine (SVM) and decision tree (DT) are applied on the seven novel indices. The results are that, seven novel indices are significantly different between the events and non-events groups, and the SVM classifier has the highest classification Acc and Spe for prediction of cardiovascular and cerebrovascular events, they are 88.31% and 90.19%, respectively. |
语种 | 英语 |
WOS记录号 | WOS:000502829700037 |
资助机构 | National key research and development program of China (grant number 2016YFE0206200) and (grant number 2017YFC0822203) |
内容类型 | 期刊论文 |
源URL | [http://ir.sia.cn/handle/173321/26058] ![]() |
专题 | 沈阳自动化研究所_机器人学研究室 |
通讯作者 | Song CH(宋纯贺) |
作者单位 | 1.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110169, China 2.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China 3.School of Computer Science and Engineering, Northeastern University, Shenyang 110819, China |
推荐引用方式 GB/T 7714 | Shao SL,Wang T,Song CH,et al. The Novel Indices of Short-Time Heart Rate Variability for Prediction of Cardiovascular and Cerebrovascular Events[J]. Journal of Medical Imaging and Health Informatics,2020,10(3):769-774. |
APA | Shao SL,Wang T,Song CH,Su Y,&Zhao H.(2020).The Novel Indices of Short-Time Heart Rate Variability for Prediction of Cardiovascular and Cerebrovascular Events.Journal of Medical Imaging and Health Informatics,10(3),769-774. |
MLA | Shao SL,et al."The Novel Indices of Short-Time Heart Rate Variability for Prediction of Cardiovascular and Cerebrovascular Events".Journal of Medical Imaging and Health Informatics 10.3(2020):769-774. |
个性服务 |
查看访问统计 |
相关权益政策 |
暂无数据 |
收藏/分享 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论