RespNet: A deep learning model for extraction of respiration from photoplethysmogram-Reference-Cited by-同舟云学术

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RespNet: A deep learning model for extraction of respiration from photoplethysmogram

Published:2019-07 Issue: Volume: Page:
ISSN:
Container-title:2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
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Author:

Ravichandran Vignesh,Murugesan Balamurali,Balakarthikeyan Vaishali,Ram Keerthi,Preejith S.P.,Joseph Jayaraj,Sivaprakasam Mohanasankar

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/8844528/8856280/08856301.pdf?arnumber=8856301

Cited by 39 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. Leveraging Attention-reinforced UWB Signals to Monitor Respiration during Sleep;ACM Transactions on Sensor Networks;2024-08-26

2. ResPara-Net: Respiration Parameter Estimation Using Wearable Single Inertial Measurement Unit Sensor and Deep Learning;IEEE Sensors Journal;2024-08-01

3. UWB-enabled Sensing for Fast and Effortless Blood Pressure Monitoring;Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies;2024-05-13

4. Contactless Blood Oxygen Saturation Estimation from Facial Videos Using Deep Learning;Bioengineering;2024-03-04

5. A Novel Respiratory Rate Estimation Algorithm from Photoplethysmogram Using Deep Learning Model;Diagnostics;2024-01-28

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