Heart rate variability classification using deep learning with dimensional reduction

doi:10.1117/12.2579588

Details of Research Outputs

Title	Heart rate variability classification using deep learning with dimensional reduction
Creator	Lin，Qinghua; Tsang，Ken K.T.
Date Issued	2020
Source Publication	Proceedings of SPIE - The International Society for Optical Engineering
ISSN	0277-786X
Volume	11584
Abstract	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.
Keyword	entropy frequency domain HRV neural network nonlinear PCA time domain
DOI	10.1117/12.2579588
URL	View source
Language	英语English
Scopus ID	2-s2.0-85097200654
Citation statistics	Cited Times [WOS]:0 [WOS Record] [Related Records in WOS]
Document Type	Conference paper
Identifier	http://repository.uic.edu.cn/handle/39GCC9TT/6200
Collection	Beijing Normal-Hong Kong Baptist University
Affiliation	Beijing Normal University-Hong Kong Baptist University-United International College,Zhuhai, Guangdong Province,China
First Author Affilication	Beijing Normal-Hong Kong Baptist University
Recommended Citation GB/T 7714	Lin，Qinghua,Tsang，Ken K.T. Heart rate variability classification using deep learning with dimensional reduction[C], 2020.

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