An Adaptive Sleep Apnea Detection Model Using Multi Cascaded Atrous-Based Deep Learning Schemes With Hybrid Artificial Humming Bird Pity Beetle Algorithm-Reference-Cited by-同舟云学术

An Adaptive Sleep Apnea Detection Model Using Multi Cascaded Atrous-Based Deep Learning Schemes With Hybrid Artificial Humming Bird Pity Beetle Algorithm

Published:2023 Issue: Volume:11 Page:113114-113133
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Aswath Selvaraj¹^ORCID,Sundaram Valarmathi Ravichandran Shanmuga¹^ORCID,Mahdal Miroslav²^ORCID

Affiliation:

1. Department of ECE, Veltech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai, India

2. Department of Control Systems and Instrumentation, Faculty of Mechanical Engineering, VSB-Technical University of Ostrava, Ostrava, Czech Republic

Funder

European Regional Development Fund through the Research Centre of Advanced Mechatronic Systems Project Within the Operational Program Research, Development, and Education

Application of Machine and Process Control Advanced Methods funded by the Ministry of Education, Youth and Sports, Czech Republic

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

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

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10264064.pdf?arnumber=10264064

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3. Sleep Spindle Detection and Prediction Using a Mixture of Time Series and Chaotic Features

4. Detection of sleep apnea using deep neural networks and single-lead ECG signals

5. Motion prediction for beating heart surgery with GRU

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