A Hierarchical Approach for the Diagnosis of Sleep Disorders Using Convolutional Recurrent Neural Network

A Hierarchical Approach for the Diagnosis of Sleep Disorders Using Convolutional Recurrent Neural Network

Sleep is an essential criterion for health. However, sleep disorders degrade the sleep quality. Hence, to diagnose sleep disorders, sleep monitoring is crucial. The cyclic alternating patterns (CAP) phases describe the sleep quality. However, CAP detection is a time-consuming, hectic, and uncertain...

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Bibliographic Details
Main Authors: Aditya Wadichar, Shruti Murarka, Dhruvi Shah, Ankit Bhurane, Manish Sharma, Hasan S. Mir, U. Rajendra Acharya
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Convolutional neural network (CNN)
cyclic alternating patterns (CAP)
deep learning
electroencephalogram (EEG)
long short-term memory (LSTM)
sleep disorders classification
Online Access:https://ieeexplore.ieee.org/document/10310136/

Internet

https://ieeexplore.ieee.org/document/10310136/

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