Detection of driver drowsiness level using a hybrid learning model based on ECG signals
Published 2023 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Detection of driver drowsiness level using a hybrid learning model based on ECG signals
Authors
Keywords
-
Journal
Biomedical Engineering-Biomedizinische Technik
Volume -, Issue -, Pages -
Publisher
Walter de Gruyter GmbH
Online
2023-10-12
DOI
10.1515/bmt-2023-0193
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Driver Monitoring of Automated Vehicles by Classification of Driver Drowsiness Using a Deep Convolutional Neural Network Trained by Scalograms of ECG Signals
- (2022) Sadegh Arefnezhad et al. Energies
- Automatic drowsiness detection for safety-critical operations using ensemble models and EEG signals
- (2022) Plínio M.S. Ramos et al. PROCESS SAFETY AND ENVIRONMENTAL PROTECTION
- Multi-Level Classification of Driver Drowsiness by Simultaneous Analysis of ECG and Respiration Signals Using Deep Neural Networks
- (2022) Serajeddin Ebrahimian et al. International Journal of Environmental Research and Public Health
- Driver sleepiness detection with deep neural networks using electrophysiological data
- (2021) Martin Hultman et al. PHYSIOLOGICAL MEASUREMENT
- A Real-Time QRS Detection Algorithm Based on Energy Segmentation for Exercise Electrocardiogram
- (2021) Hui Xiong et al. CIRCUITS SYSTEMS AND SIGNAL PROCESSING
- An intelligent computer-aided approach for atrial fibrillation and atrial flutter signals classification using modified bidirectional LSTM network
- (2021) Jibin Wang INFORMATION SCIENCES
- Fatigue Monitoring Through Wearables: A State-of-the-Art Review
- (2021) Neusa R. Adão Martins et al. Frontiers in Physiology
- Physiological signal-based drowsiness detection using machine learning: Singular and hybrid signal approaches
- (2021) Md Mahmudul Hasan et al. JOURNAL OF SAFETY RESEARCH
- Heart Rate Variability for Classification of Alert Versus Sleep Deprived Drivers in Real Road Driving Conditions
- (2020) Anna Persson et al. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
- Classification of pilots’ mental states using a multimodal deep learning network
- (2019) Soo-Yeon Han et al. Biocybernetics and Biomedical Engineering
- A survey on ECG analysis
- (2018) Selcan Kaplan Berkaya et al. Biomedical Signal Processing and Control
- Detection of mental fatigue state with wearable ECG devices
- (2018) Shitong Huang et al. INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS
- Avionics Human-Machine Interfaces and Interactions for Manned and Unmanned Aircraft
- (2018) Yixiang Lim et al. PROGRESS IN AEROSPACE SCIENCES
- Unobtrusive Vital Sign Monitoring in Automotive Environments—A Review
- (2018) Steffen Leonhardt et al. SENSORS
- Detecting driving stress in physiological signals based on multimodal feature analysis and kernel classifiers
- (2017) Lan-lan Chen et al. EXPERT SYSTEMS WITH APPLICATIONS
- Smartwatch-Based Driver Vigilance Indicator With Kernel-Fuzzy-C-Means-Wavelet Method
- (2016) Boon Giin Lee et al. IEEE SENSORS JOURNAL
- A comparative evaluation of neural network classifiers for stress level analysis of automotive drivers using physiological signals
- (2013) Rajiv Ranjan Singh et al. Biomedical Signal Processing and Control
- Applying neural network analysis on heart rate variability data to assess driver fatigue
- (2010) M. Patel et al. EXPERT SYSTEMS WITH APPLICATIONS
- Driver Drowsiness Classification Using Fuzzy Wavelet-Packet-Based Feature-Extraction Algorithm
- (2010) R N Khushaba et al. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
Publish scientific posters with Peeref
Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.
Learn MoreFind the ideal target journal for your manuscript
Explore over 38,000 international journals covering a vast array of academic fields.
Search