Enhanced Pilot Attention Monitoring: A Time-Frequency EEG Analysis Using CNN–LSTM Networks for Aviation Safety
Despite significant technological advancements in aviation safety systems, human-operator condition monitoring remains a critical challenge, with more than 75% of aircraft incidents stemming from attention-related perceptual failures. This study addresses a fundamental question in sensor-based condi...
Saved in:
| Main Authors: | Quynh Anh Nguyen, Nam Anh Dao, Long Nguyen |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-06-01
|
| Series: | Information |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2078-2489/16/6/503 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Predicting depression risk in middle-aged and elderly adults in China using CNN-BiLSTM-Attention mechanism and LSTM+SHAP framework
by: Shengxian Bi, et al.
Published: (2025-08-01) -
Performance Enhancement of EEG Signatures for Person Authentication Using CNN BiLSTM Method
by: Ashish Ranjan Mishra, et al.
Published: (2024-11-01) -
Hybrid LSTM–Attention and CNN Model for Enhanced Speech Emotion Recognition
by: Fazliddin Makhmudov, et al.
Published: (2024-12-01) -
Speech Emotion Recognition: Comparative Analysis of CNN-LSTM and Attention-Enhanced CNN-LSTM Models
by: Jamsher Bhanbhro, et al.
Published: (2025-05-01) -
Air quality prediction enhanced by a CNN-LSTM-Attention model optimized with an advanced dung beetle algorithm
by: Xiaojie Zhou, et al.
Published: (2025-08-01)