IoT-Enabled Respiratory Pattern Monitoring in Critical Care: A Real-Time Recurrent Neural Network Approach-Reference-Cited by-同舟云学术

IoT-Enabled Respiratory Pattern Monitoring in Critical Care: A Real-Time Recurrent Neural Network Approach

Published:2024-04-12 Issue: Volume: Page:508-513
ISSN:
Container-title:2024 10th International Conference on Communication and Signal Processing (ICCSP)
language:
Short-container-title:

Author:

Rajarajan S.¹,Kalaivani R.²,Kaliammal N.³,Saravanan S.T.⁴,Ilampiray P⁵,Srinivasan C.⁶

Affiliation:

1. Sri Sai Ram Institute of Technology,Department of Electronics and Communication Engineering,Chennai,Tamil Nadu,India

2. MIT College of Arts and Science for Women Musiri,Trichy,Tamil Nadu,India

3. Muthayammal Engineering College, (Autonomous),Department of Electronics and Communication Engineering,Rasipuram, Namakkal,Tamil Nadu,India

4. Sphoorthy Engineering College,Department of CSE-Cyber Security,Hyderabad,Telangana,India

5. R.M.K. Engineering College,Department of Computer Science and Engineering,Chennai,Tamil Nadu,India

6. Saveetha Institute of Medical and Technical Sciences, Saveetha University,Saveetha School of Engineering,Department of Computer Science and Engineering,Chennai,Tamil Nadu,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10543256/10543221/10543359.pdf?arnumber=10543359

Reference20 articles.

1. Internet-of-Things-Based Sensor Module for Respiratory Tracking System

2. Becalm: Intelligent Monitoring of Respiratory Patients

3. Enhancing Text Input for Motor Disabilities through IoT and Machine Learning: A Focus on the Swipe-to-Type Algorithm

4. IoT-Driven Image Recognition for Microplastic Analysis in Water Systems using Convolutional Neural Networks

5. Bayesian decision model based reliable route formation in internet of things