Deep neural network based missing data prediction of electrocardiogram signal using multiagent reinforcement learning-Reference-Cited by-同舟云学术

Deep neural network based missing data prediction of electrocardiogram signal using multiagent reinforcement learning

Published:2021-05 Issue: Volume:67 Page:102508
ISSN:1746-8094
Container-title:Biomedical Signal Processing and Control
language:en
Short-container-title:Biomedical Signal Processing and Control

Author:

Banerjee Soumyendu^ORCID,Singh Girish Kumar

Funder

Indian Institute of Technology Roorkee

Publisher

Elsevier BV

Subject

Health Informatics,Signal Processing

Reference27 articles.

1. Textbook of Clinical Echocardiography;Otto,2018

2. Data reconstruction for missing electrocardiogram using linear predictive coding;Theera-Umpon,2008

3. Reconstruction of ECG signals in presence of corruption;Ganeshapillai,2011

4. Principal component analysis based method for reconstruction of fragments of corrupted or lost signal in multilead data reflecting electrical heart activity and hemodynamics;Petrolis;Comp. Cardi. Belfast,2010

5. Identifying IIR filter coefficients using particle swarm optimization with application to reconstruction of missing cardiovascular signals;Hartmann;Eng. Appl. Art. Intell.,2014

Cited by 20 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Reconstruction of Missing Electrocardiography Signals from Photoplethysmography Data Using Deep Neural Network;Bioengineering;2024-04-11

2. Einführung in nicht-invasive biomedizinische Signale für die Gesundheitsversorgung;Fortschritte in der nicht-invasiven biomedizinischen Signalverarbeitung mit ML;2024

3. Real-Time PPG-to-ECG Reconstruction Model With On-Device Recalibration Facility;IEEE Transactions on Instrumentation and Measurement;2024

4. Transfer Learning with CNN-LSTM for detection of Cardiac Events in Arrhythmia Disease;2023 Seventh International Conference on Image Information Processing (ICIIP);2023-11-22

5. Reinforcement learning algorithms: A brief survey;Expert Systems with Applications;2023-11