Real-Time Classification of Deep and Non-Deep Sleep With Comparative Intervention Experiments
Sleep is an essential part of human life, and sleep quality is a critical indicator of overall health. This paper presents a system that utilizes a Brain-Computer Interface and a Deep Learning Network for the real-time classification of non-deep sleep and deep sleep. By collecting, uploading, prepro...
Saved in:
Main Authors: | Mo Xia, Hongxi Xue, Boning Li, Jianting Cao |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2025-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10788712/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Real-Time Multi-Task Deep Learning Model for Polyp Detection, Characterization, and Size Estimation
by: Phanukorn Sunthornwetchapong, et al.
Published: (2025-01-01) -
EEG electrode setup optimization using feature extraction techniques for neonatal sleep state classification
by: Hafza Ayesha Siddiqa, et al.
Published: (2025-01-01) -
USSD: Unsupervised Sleep Spindle Detector
by: Edgardo Ramirez, et al.
Published: (2025-01-01) -
Deep characteristic learning model for real-time flow monitoring based on H-ADCP
by: Yu Li, et al.
Published: (2025-02-01) -
Exploring the Effectiveness of Machine Learning and Deep Learning Techniques for EEG Signal Classification in Neurological Disorders
by: Souhaila Khalfallah, et al.
Published: (2025-01-01)