Heart rate variability classification using deep learning with dimensional reduction

doi:10.1117/12.2579588

科研成果详情

题名	Heart rate variability classification using deep learning with dimensional reduction
作者	Lin，Qinghua; Tsang，Ken K.T.
发表日期	2020
会议录名称	Proceedings of SPIE - The International Society for Optical Engineering
ISSN	0277-786X
卷号	11584
摘要	Heart rate variability (HRV) refers to the variation of the heart rate cycles, which contains information of how the autonomic nerves system regulates the cardiovascular system. HRV is a valuable indicator to diagnose various cardiovascular diseases and predict arrhythmia events. This study is based on the standardized five-minute and ten-minute RR interval series from the open source Electrocardiogram (ECG) database website PhysioNet. Artificial Neural Networks (ANN) are used to distinguish patients with congestive heart failure or atrial fibrillation from normal sinus rhythm utilizing features calculated by time and frequency domains as well as nonlinear analysis. To eliminate redundancy and avoid overfitting, Principal Component Analysis (PCA) is performed to screen for the most efficient features. PCA not only improves the accuracy but also greatly reduces the number of nodes in the ANN model, thus, improves the efficiency. Overall, ANN classifiers achieved an accuracy of 79% for five-minute RR interval series and 84% for that of ten-minute series. The performance of Random Forest (RF) classifier is not as satisfactory. However, its list of most important features indicates nonlinear dynamics may play an important role and provide useful insights to the classification problem.
关键词	entropy frequency domain HRV neural network nonlinear PCA time domain
DOI	10.1117/12.2579588
URL	查看来源
语种	英语English
Scopus入藏号	2-s2.0-85097200654
引用统计	被引频次[WOS]：0 [WOS记录] [WOS相关记录]
文献类型	会议论文
条目标识符	https://repository.uic.edu.cn/handle/39GCC9TT/6200
专题	北师香港浸会大学
作者单位	Beijing Normal University-Hong Kong Baptist University-United International College,Zhuhai, Guangdong Province,China
第一作者单位	北师香港浸会大学
推荐引用方式 GB/T 7714	Lin，Qinghua,Tsang，Ken K.T. Heart rate variability classification using deep learning with dimensional reduction[C], 2020.