Real‐time photoplethysmographic heart rate measurement using deep neural network filters-Reference-Cited by-同舟云学术

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Real‐time photoplethysmographic heart rate measurement using deep neural network filters

Published:2021-10 Issue:5 Volume:43 Page:881-890
ISSN:1225-6463
Container-title:ETRI Journal
language:en
Short-container-title:ETRI Journal

Author:

Kim Ji Woon¹,Park Sung Min²,Choi Seong Wook¹³^ORCID

Affiliation:

1. Interdisciplinary Program in Biohealth‐Machinery Convergence Engineering Kangwon National University Chuncheon Rep. of Korea

2. School of Medicine Kangwon National University Chuncheon Rep. of Korea

3. Program of Mechanical and Biomedical Engineering, College of Engineering Kangwon National University Chuncheon Rep. of Korea

Funder

Ministry of SMEs and Startups

National Research Foundation of Korea

Publisher

Wiley

Subject

Electrical and Electronic Engineering,General Computer Science,Electronic, Optical and Magnetic Materials

Link

https://onlinelibrary.wiley.com/doi/pdf/10.4218/etrij.2020-0394

Reference32 articles.

1. A comparison of photoplethysmography and ECG recording to analyse heart rate variability in healthy subjects

2. Verylow frequency variability in arterial blood pressure and blood volume pulse

3. Influence of arterial pulse and reflected waves on blood pressure and cardiac function

4. A Machine Learning-Empowered System for Long-Term Motion-Tolerant Wearable Monitoring of Blood Pressure and Heart Rate With Ear-ECG/PPG

5. Computerized photo-plethysmography of the finger

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3. Counter-pulsation Control of a Pulsatile Extracorporeal Membrane Oxygenator Device using Deep Neural Networks for Blood Pressure Waveform Analysis;2024-01-29

4. Development of an Automatic Pill Image Data Generation System;Healthcare Informatics Research;2023-01-31

5. DNN based reliability evaluation for telemedicine data;Biomedical Engineering Letters;2022-10-11

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