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Brain Signal Based Driver Drowsiness Prediction

Addzrull Hi-Fi Syam Ahmad Jamil, Mohd Lutfi Mohd Khidir, Mohd Firdaus Mohd Mokhtar
2020 International Journal of Academic Research in Business and Social Sciences  
Therefore, in this research work, it is proposed to develop an adaptive heavy vehicle driver fatigue and alertness model based on EEG frequency bands by combining signal processing algorithms and soft  ...  computing techniques such as Neuro-fuzzy algorithm to estimate the driver cognitive state while driving a vehicle in a virtual reality (VR)-based dynamic simulator under monotonous driving environment.  ...  EEG signals and Neuro-fuzzy are used to estimate the driver's condition while using the driving simulator.  ... 
doi:10.6007/ijarbss/v10-i11/8835 fatcat:auunctrtxbfmpmztwl7xg4xmri

Brain Signal Based Driver Drowsiness Prediction

Addzrull Hi-Fi Syam Ahmad Jamil, Mohd Lutfi Mohd Khidir, Mohd Firdaus Mohd Mokhtar
2021 International Journal of Academic Research in Business and Social Sciences  
EEG signals and Neuro-fuzzy are used to estimate the driver's condition while using the driving simulator.  ...  EEG based identification of alertness levels have the advantages in making accurate and quantitative assessment and relatively shorter one to track second-to-second fluctuations in the driver's performance  ... 
doi:10.6007/ijarbss/v11-i2/8616 fatcat:46py4sy2dzczbpcsj2cwtdzita

Generalized EEG-Based Drowsiness Prediction System by Using a Self-Organizing Neural Fuzzy System

Fu-Chang Lin, Li-Wei Ko, Chun-Hsiang Chuang, Tung-Ping Su, Chin-Teng Lin
2012 IEEE Transactions on Circuits and Systems Part 1: Regular Papers  
A generalized EEG-based Neural Fuzzy system to predict driver's drowsiness was proposed in this study.  ...  others, in this study, we proposed a generalized EEG-based Self-organizing Neural Fuzzy system to monitor and predict the driver's drowsy state with the occipital area.  ...  In [17] , an independent component analysis-based (ICA-based) Fuzzy Neural Networks was proposed based on the independent sources instead of the scalp EEG activities.  ... 
doi:10.1109/tcsi.2012.2185290 fatcat:ojexaudwpnefvegcftg4qcqlam

Current Status and Future Research Directions in Monitoring Vigilance of Individual or Mass Audience in Monotonous Working Environment

B.F Momin
2012 International Journal of Soft Computing  
This paper reviews and compares current status of research in modelling fatigue where fatigue is modelled using probabilistic models, machine learning models, finite state machine etc.  ...  Therefore early detection of fatigued state has become essential in monotonous working environments like driving vehicle, operating machines etc.  ...  Then the selected alpha-band features are fed to the self-constructing neural fuzzy inference network (SONFIN) to learn the relationship between the EEG spectra and driving performance.  ... 
doi:10.5121/ijsc.2012.3204 fatcat:kuoow2ez4nctdp6womly5wijm4

EEG-based analysis of human driving performance in turning left and right using Hopfield neural network

Mitra Taghizadeh-Sarabi, Kavous Niksirat, Sohrab Khanmohammadi, Mohammadali Nazari
2013 SpringerPlus  
In this article a quantitative analysis was devised assessing driver's cognition responses by exploring the neurobiological information underlying electroencephalographic (EEG) brain signals in a left  ...  The driving pathway has been selected with no obstacles, a set of indicators are used to inform the subjects when they had to turn left or right by means of keyboard left and right arrows.  ...  Acknowledgments Thanks from Paarand specialized center for human enhancement for providing driving simulation systems and data collection.  ... 
doi:10.1186/2193-1801-2-662 pmid:24353979 pmcid:PMC3866377 fatcat:senxhm33pzdb3ft6d3rmifv4ue

A Proposed System for Vehicle Monitoring, Accident Detection and Prevention using IOT

Mr. C. Balakrishnan
2019 International Journal for Research in Applied Science and Engineering Technology  
The rate of vehicular accidents in our country is keep on getting increased mainly because of driver's carelessness. Drowsiness and alcoholic state of the driver are the main reasons among them.  ...  In spite of this prevention, if accident occurs, the situation can be analyzed by the use of vibration sensor and the message can be sent to the emergency services through Internet Of Things (IOT).  ...  A summed up to screens and foresee the driver's-tired state we use EEG-based Self-sorting out Neural Fuzzy framework.  ... 
doi:10.22214/ijraset.2019.3198 fatcat:jw533wocmzhq3kqejgf7r4xoqa

Data Fusion to Develop a Driver Drowsiness Detection System with Robustness to Signal Loss

Sajjad Samiee, Shahram Azadi, Reza Kazemi, Ali Nahvi, Arno Eichberger
2014 Sensors  
A driving simulator is used to gather real data and then artificial neural networks are used in the structure of the designed system.  ...  In order to avoid driving distraction, any use of an intrusive method is prevented.  ...  Acknowledgments The authors want to thank all the drivers that participated in the tests and all people in the virtual laboratory of K.N. Toosi University of Technology who helped us doing the tests.  ... 
doi:10.3390/s140917832 pmid:25256113 pmcid:PMC4208253 fatcat:b4obrbj2pzf6fks4nqo4cus4fq

A Smartphone-Based Driver Safety Monitoring System Using Data Fusion

Boon-Giin Lee, Wan-Young Chung
2012 Sensors  
A Fuzzy Bayesian framework is designed to indicate the driver's capability level and is updated continuously in real-time.  ...  This paper proposes a method for monitoring driver safety levels using a data fusion approach based on several discrete data types: eye features, bio-signal variation, in-vehicle temperature, and vehicle  ...  a Fuzzy Bayesian network in a smartphone device to predict the driver's aptitude and alertness state over time; (4) a low-cost solution for capturing the driver's image using the front-facing video sensor  ... 
doi:10.3390/s121217536 pmid:23247416 pmcid:PMC3571852 fatcat:6hglwqwsbvezvnfdjqqacbzsje

Drowsiness Warning System Using Artificial Intelligence

Nidhi Sharma, V. K. Banga
2010 Zenodo  
It is important for driving support systems to detect status of driver's consciousness. Particularly, detecting driver's drowsiness could prevent drivers from collisions caused by drowsy driving.  ...  This system is based on facial images analysis for warning the driver of drowsiness or in attention to prevent traffic accidents.  ...  A neural network computer system was used to capture a driver's face and eye area.  ... 
doi:10.5281/zenodo.1080382 fatcat:5r6molxgynbihm7eoueufayvwq

Estimating Driving Performance Based on EEG Spectrum Analysis

Chin-Teng Lin, Ruei-Cheng Wu, Tzyy-Ping Jung, Sheng-Fu Liang, Teng-Yi Huang
2005 EURASIP Journal on Advances in Signal Processing  
models to indirectly estimate driver's drowsiness level in a virtual-reality-based driving simulator.  ...  Our results demonstrated that it is feasible to accurately estimate quantitatively driving performance, expressed as deviation between the center of the vehicle and the center of the cruising lane, in  ...  This work was supported in part by the Ministry of Education, Taiwan, under Grant EX-91-E-FAOE-4-4 and Ministry of Economic Affairs, Taiwan, under Grant 93-17-A-02-S1-032 to C. T.  ... 
doi:10.1155/asp.2005.3165 fatcat:2salzlljsjgnjo5hmifnbarfqa

Computational intelligent brain computer interaction and its applications on driving cognition

Chin-Ten Lin, Li-Wei Ko, Tzu-Kuei Shen
2009 IEEE Computational Intelligence Magazine  
cognitive-state monitoring of the driver performing the realistic long-term driving tasks in a simulated realistic-driving environment; and (2) to extract the brain dynamic changes of driver's distraction  ...  Driving is one of the most common attention-demanding tasks in daily life. Driver's fatigue, drowsiness, inattention, and distraction are reported a major causal factor in many traffic accidents.  ...  Duann, and R. S. Hunag in University of California, San Diego, for their suggestions and consultation, and also thank S. A. Chen, T. Y. Huang, J. L. Jeng, H. S. Huang, and T. T.  ... 
doi:10.1109/mci.2009.934559 fatcat:ilrufdbvbzawdl3qo5cw3oyrru


A.D. Jeyarani, Reena Daphne, Chettiyar Vani Vivekanand
These actions are provided by the EEG and EOG signal brain actions. From the EEG and EOG signals the peculiarities like mean, peak, pitch, maximum, minimum, standard deviation are assessed .  ...  These are then subjected to fuzzy based classification to give a precise result checking over the maximum values in the alpha and the beta series .  ...  Fu-Chang Lin et al [20] have proposed a summed up EEG-based Neural Fuzzy framework to conjecture driver's drowsiness.  ... 
doi:10.24297/jac.v13i9.5804 fatcat:k7j6h7qqrvfxriffhm7p4cijyy

EEG-based Safety Driving Performance Estimation and Alertness Using Support Vector Machine

Hongyu Sun, Lijun Bi, Bisheng Chen, Yinjing Guo
2015 International Journal of Security and Its Applications  
Safety driving performance estimation and alertness (SDPEA) has drawn the attention of researchers in preventing traffic accidents caused by drowsiness while driving.  ...  This paper presents an effective EEG-based driver drowsiness monitoring system by analyzing the changes of brain activities in a simulator driving environment.  ...  It has been used to assess the driver's performance for many years.  ... 
doi:10.14257/ijsia.2015.9.6.13 fatcat:2mwa7xthcfdwfibq2fk24gjtl4

Driver Fatigue Detection Systems Using Multi-Sensors, Smartphone, and Cloud-Based Computing Platforms: A Comparative Analysis

Qaisar Abbas, Abdullah Alsheddy
2020 Sensors  
Moreover, we performed state-of-the-art comparisons by using driving simulators to incorporate multimodal features of the driver.  ...  In this paper, we reviewed state-of-the-art approaches for predicting unsafe driving styles using three common IoT-based architectures.  ...  Acknowledgments: The authors would like to thank for KACST funding organization to support this research and researchers to provide us different EEG datasets for performing experiments.  ... 
doi:10.3390/s21010056 pmid:33374270 pmcid:PMC7796320 fatcat:uhgbzmfujrbb7nsilzprs3hrim

Developing and evaluating a mobile driver fatigue detection network based on electroencephalograph signals

Jinghai Yin, Jianfeng Hu, Zhendong Mu
2017 Healthcare technology letters  
The application can be used for the driver to detect the state of his/her fatigue based on EEG signals, and warn neighbourhood vehicles.  ...  (iii) The detection algorithm for driver fatigue is applied based on fuzzy entropy. The idea of 10-fold crossvalidation and support vector machine are used for classified calculation.  ...  In this work, we developed and evaluated a mobile driver fatigue detection network based on EEG signals. 2.  ... 
doi:10.1049/htl.2016.0053 pmid:28529761 pmcid:PMC5435952 fatcat:jnacippsonduvcxwqzxkaxkle4
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