ArticleSensors (Basel, Switzerland)2021
Convolutional Neural Network for Drowsiness Detection Using EEG Signals.
Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed, 115 citations in OpenAlex.
- Subject Identity Confounds qEEG Emotion Recognition on DEAP and DREAMER.Sensors (Basel, Switzerland) · 2026Article
- Application of Filter Bank to Improve Fatigue Monitoring in Wearable EEG-Based Brain-Computer Interface.NeuroSci · 2026Article
- Sensing Technologies and Physiological Parameters for Real-Time Driver Drowsiness Detection: A Comprehensive Review.Sensors (Basel, Switzerland) · 2026Review
- SE-Driven Dynamic Convolution for Adaptive EEG-Based Driver Fatigue Detection Across Spectral, Spatial, and Temporal Domains.Sensors (Basel, Switzerland) · 2026Article
- Driver Drowsiness Detection using Machine Learning and Deep Learning Techniques: A Systematic Review.Archives of academic emergency medicine · 2026Article
- Discrete wavelet transform-driven optimized deep learning-based framework for dyslexia detection using EEG signals.Frontiers in neuroinformatics · 2026Article
- Research on the Prediction of Driver Fatigue Degree Based on EEG Signals.Sensors (Basel, Switzerland) · 2025Article
- An improved feature extraction algorithm for EEG-based driving fatigue recognition.Scientific reports · 2025Article
- STFTransNet: A Transformer Based Spatial Temporal Fusion Network for Enhanced Multimodal Driver Inattention State Recognition System.Sensors (Basel, Switzerland) · 2025Article
- Enhancing convolutional neural networks in electroencephalogram driver drowsiness detection using human inspired optimizers.Scientific reports · 2025Article
- Article
- Artificial Intelligence-Powered Electronic Skin.Nature machine intelligence · 2023Article
- A Deep Learning Approach to Classify Sitting and Sleep History from Raw Accelerometry Data during Simulated Driving.Sensors (Basel, Switzerland) · 2022Article
- Non-smooth Bayesian learning for artificial neural networks.Journal of ambient intelligence and humanized computing · 2022Article
- Driver drowsiness estimation using EEG signals with a dynamical encoder-decoder modeling framework.Scientific reports · 2022Article
- Trends and Future Prospects of the Drowsiness Detection and Estimation Technology.Sensors (Basel, Switzerland) · 2021Review
- Efficient Gradient Updating Strategies with Adaptive Power Allocation for Federated Learning over Wireless Backhaul.Sensors (Basel, Switzerland) · 2021Article
- Deep Convolutional Neural Network Regularization for Alcoholism Detection Using EEG Signals.Sensors (Basel, Switzerland) · 2021Article
- A Review of EEG Signal Features and their Application in Driver Drowsiness Detection Systems.Sensors (Basel, Switzerland) · 2021Review
Corrections and comments
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Authors and funding
6 authors at 4 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Drowsiness detection (DD) has become a relevant area of active research in biomedical signal processing. Recently, various deep learning (DL) researches based on the EEG signals have been proposed to detect fatigue conditions. The research presented in this paper proposes an EEG classification system for DD based on DL networks. However, the proposed DD system is mainly realized into two procedures; (i) data acquisition and (ii) model analysis. For the data acquisition procedure, two key steps are considered, which are the signal collection using a wearable
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.