Application of a convolutional neural network for predicting the occurrence of ventricular tachyarrhythmia using heart rate variability features (vol 10, 6769, 2020)

被引：0
|
作者：
Taye, Getu Tadele
Hwang, Han-Jeong
Lim, Ki Moo
机构：
[1] Health Informatics Unit, School of Public Health, Mekelle University, Mekelle
[2] Department of Electronics and Information Engineering, Korea University, Sejong
[3] Department of IT Convergence Engineering, Kumoh Institute of Technology, Gumi
来源：
SCIENTIFIC REPORTS | 2020年 / 10卷 / 01期
基金：
新加坡国家研究基金会;
关键词：
D O I：
10.1038/s41598-020-68530-0
中图分类号：
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号：
07 ; 0710 ; 09 ;
摘要：
An amendment to this paper has been published and can be accessed via a link at the top of the paper.
引用
收藏
页数：2
相关论文
共 50 条
  • [21] Heart rate variability analysis using neural network models for automatic detection of lifestyle activities
    Matta, Sarah Christina
    Sankari, Ziad
    Rihana, Sandy
    BIOMEDICAL SIGNAL PROCESSING AND CONTROL, 2018, 42 : 145 - 157
  • [22] Deep Neural Network Sleep Scoring Using Combined Motion and Heart Rate Variability Data
    Haghayegh, Shahab
    Khoshnevis, Sepideh
    Smolensky, Michael H.
    Diller, Kenneth R.
    Castriotta, Richard J.
    SENSORS, 2021, 21 (01) : 1 - 14
  • [23] Using neural network to recognize human emotions from heart rate variability and skin resistance
    Lee, ChungK
    Yoo, S. K.
    Park, YoonJ
    Kim, NamHyun
    Jeong, KeeSam
    Lee, ByungChae
    2005 27TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-7, 2005, : 5523 - 5525
  • [24] Heart rate variability-derived features based on deep neural network for distinguishing different anaesthesia states
    Zhan, Jian
    Wu, Zhuo-xi
    Duan, Zhen-xin
    Yang, Gui-ying
    Du, Zhi-yong
    Bao, Xiao-hang
    Li, Hong
    BMC ANESTHESIOLOGY, 2021, 21 (01)
  • [25] Arrhythmia detection based on time–frequency features of heart rate variability and back-propagation neural network
    Ram Sewak Singh
    Barjinder Singh Saini
    Ramesh Kumar Sunkaria
    Iran Journal of Computer Science, 2019, 2 (4) : 245 - 257
  • [26] Heart rate variability-derived features based on deep neural network for distinguishing different anaesthesia states
    Jian Zhan
    Zhuo-xi Wu
    Zhen-xin Duan
    Gui-ying Yang
    Zhi-yong Du
    Xiao-hang Bao
    Hong Li
    BMC Anesthesiology, 21
  • [27] Efficient Extraction of Deep Image Features Using a Convolutional Neural Network (CNN) for Detecting Ventricular Fibrillation and Tachycardia
    Mjahad, Azeddine
    Saban, Mohamed
    Azarmdel, Hossein
    Rosado-Munoz, Alfredo
    JOURNAL OF IMAGING, 2023, 9 (09)
  • [28] Using convolutional neural network online estimators for predicting pain-level variability enables predictive control of anesthesia
    Heynen, Joren
    Copot, Dana
    Ghita, Mihaela
    Ionescu, Clara
    2021 25TH INTERNATIONAL CONFERENCE ON SYSTEM THEORY, CONTROL AND COMPUTING (ICSTCC), 2021, : 194 - 199
  • [29] Artificial Neural Network Application in Classifying the Left Ventricular Function of the Human Heart Using Echocardiography
    Upendra, K. E. T.
    Ranaweera, G. A. C.
    Samaradiwakara, N. H. A. P.
    Munasinghe, Aruna
    Jayaratne, K. L.
    Wickramasinghe, M. I. E.
    2018 NATIONAL INFORMATION TECHNOLOGY CONFERENCE (NITC), 2018,
  • [30] Noninvasive Glucose Measurement Using Machine Learning and Neural Network Methods and Correlation with Heart Rate Variability
    Gusev, Marjan
    Poposka, Lidija
    Spasevski, Gjoko
    Kostoska, Magdalena
    Koteska, Bojana
    Simjanoska, Monika
    Ackovska, Nevena
    Stojmenski, Aleksandar
    Tasic, Jurij
    Trontelj, Janez
    JOURNAL OF SENSORS, 2020, 2020
12345