Sistemas de detección de somnolencia en conductores: inicio, desarrollo y futuro

María Agustina Garcés; José de Jesús Salgado; Jesus Andres Cruz; William Henry Cañon

doi:10.25054/22161325.717

Driver drowsiness detection systems: Beginning, development and future

Ver / Descargar

PDF (Español (España))

FLIP

HTML (Español (España))

How to Cite

Garcés, M. A., Salgado, J. de J., Cruz, J. A., & Cañon, W. H. (2015). Driver drowsiness detection systems: Beginning, development and future. Ingeniería Y Región, 13(1), 159–168. https://doi.org/10.25054/22161325.717

More Citation Formats

ACM ACS APA ABNT Chicago Harvard IEEE MLA Turabian Vancouver

Download Citation

Endnote/Zotero/Mendeley (RIS) BibTeX

Published: Sep 9, 2015

Doi

https://doi.org/10.25054/22161325.717

Dimensions

PlumX

Issue

Vol. 13 (2015)

Section

Articles

License terms / See

Declaración de originalidad y cesión de derechos para la difusión del artículo

Esta obra está bajo una Licencia Creative Commons Reconocimiento-NoComercial-CompartirIgual

María Agustina Garcés Universidad Nacional de San Juan

José de Jesús Salgado Universidad Surcolombiana

Jesus Andres Cruz Universidad Surcolombiana

William Henry Cañon Universidad Surcolombiana

Abstract

Traffic and industrial accidents are caused by many different factors. Some are due to human error and others, mechanical failure. In an effort to protect lives, many systems have been invented to minimize the impact of such accidents; however, prevention is now understood as more important than minimizing damage after the accident has already taken place. Among the most common human errors that lead to accidents is when a driver or industrial operator is overtired, fatigued or feeling drowsy. Research on this subject began 60 years ago and has developed numerous innovative time systems for detecting states of drowsiness in people using computer vision techniques. There has also been a rising interest in the analysis of brain signals that very precisely determine the different stages of sleep. This paper will review each of the techniques used to detect drowsiness and their importance as active prevention systems for traffic and industrial accidents.

Keywords

Drowsiness

Computer Vision

brain signals

active systems.

Downloads

Download data is not yet available.

Author Biographies / See

María Agustina Garcés, Universidad Nacional de San Juan

Doctora en Control Automático. Profesora Universidad Nacional de San Juan. San Juan, Argentina

José de Jesús Salgado, Universidad Surcolombiana

Magister en Ingeniería Electrónica y de Computadores. Profesor Universidad Surcolombiana. Neiva, Colombia – IEEE
Member

Jesus Andres Cruz, Universidad Surcolombiana

Estudiante Ingeniería Electrónica. Presidente Rama Estudiantil IEEE USCO, Universidad Surcolombiana – IEEE Member,

William Henry Cañon, Universidad Surcolombiana

Estudiante Ingeniería Electrónica, Universidad Surcolombiana – IEEE Member

References

Akben S.B., Subas, A. y KIymIk M.K. Comparison of artificial neural network and support vector machine classification methods in diagnosis of migraine by using EEG [Conferencia] // Signal Processing and Communications Applications Conference (SIU), 2010 IEEE 18th. 2010, pp. 637-640. DOI: 10.1109/SIU.2010.5651470.

Alipoor M., Pooyan M. y Suratgar Amir Abolfazl Classification of EEG signals in four groups, including healthy subjects with open/closed eyes and epilepsy subjects with/without seizure by PSD estimate (using the multitaper method) and ANN [Conferencia] // Health Informatics and Bioinformatics (HIBIT), 2010 5th International Symposium on. 201, pp. 98-103. DOI: 10.1109/HIBIT.2010. 5478900.

Alonso Luis Fernando Nicolás. Clasificación de características de electroencefalogramas en sistemas Brain Computer Interface basados en ritmos sensoriomotores [Informe] : Master’s thesis / UNIVERSIDAD DE VALLADOLID. 2011.

Alshaqaqi B. [y otros] Driver drowsiness detection system [Conferencia] // Systems, Signal Processing and their Applications (WoSSPA), 2013 8th International Workshop on. 2013, pp. 151-155. DOI: 10.1109/WoSSPA.2013.6602353.

Arnin J. [y otros] Wireless-based portable EEG-EOG monitoring for real time drowsiness detection [Conferencia] // Engineering in Medicine and Biology Society (EMBC), 2013 35th Annual International Conference of the IEEE. 2013, pp. 4977-4980. ISSN: 1557-170X DOI: 10.1109/EMBC.2013. 6610665.

Bermúdez Germán Rodríguez [y otros] Técnicas de reconocimiento de patrones para la clasificación de señales EEG en sistemas BCI [Conferencia] // V Jornadas de Introducción a la investigación en la UPCT 2012/ed. de Cartagena Universidad Politécnica. 2012, 5(3).

Borghini Gianluca [y otros] Measuring neurophysiological signals in aircraft pilots and car drivers for the assessment of mental workload, fatigue and drowsiness [Publicación periódica] // Neuroscience & Biobehavioral Reviews. 2014, 44, pp. 58-75. Applied Neuroscience: Models, methods, theories, reviews. A Society of Applied Neuroscience (SAN) special issue. ISSN: 0149-7634 DOI: http://dx.doi. org/10.1016/j.neubiorev.2012.10.003.

Cyganek BogusÅ‚aw y GruszczyÅ, ski SÅ‚ awomir Hybrid computer vision system for drivers’ eye recognition and fatigue monitoring [Publicación periódica] // Neurocomputing. 2014, 126, pp. 78-94. Recent trends in Intelligent Data Analysis Selected papers of the The 6th International Conference on Hybrid Artificial Intelligence Systems (HAIS 2011) Online Data Processing Including a selection of papers from the International Conference on Adaptive and Intelligent Systems 2011 (ICAIS 2011). ISSN: 0925-2312 DOI: http://dx.doi.org/10.1016/j.neucom.2013.01.048.

Danisman T. [y otros] Drowsy driver detection system using eye blink patterns [Conferencia] //Machine and Web Intelligence ICMWI), 2010 International Conference on. 2010, pp. 230-233. DOI: 10.1109/ICMWI.2010.5648121.166 Revista Ingeniería y Región. 2015;13(1):159-168 Sistemas de detección de somnolencia en conductores... / Garcés & Cols.

Daphne R. Reena y Raj A. Albert A Drowsiness Detection Architecture using Feature Extraction Methodology [Publicación periódica] // Procedia Engineering. 2012, 38, pp. 959-963. {INTERNATIONAL} {CONFERENCE} {ON} {MODELLING} {OPTIMIZATION} {AND}

{COMPUTING}. ISSN: 1877-7058 DOI: http://dx.doi.org/10.1016/j.proeng.2012. 06.121.

Dawson Drew, Searle Amelia K. y Paterson Jessica L. Look before you (s)leep: Evaluating the use of fatigue detection technologies within a fatigue risk management system for the road transport industry [Publicación periódica] // Sleep Medicine Reviews. 2014, 2, 18, pp. 141-152. ISSN: 1087-0792 DOI: http://dx.doi.org/10.1016/j.smrv.2013. 03.003.

Delgado Saa J.F. y Cetin M. Discriminative Methods for Classification of Asynchronous Imaginary Motor Tasks From EEG Data [Publicación periódica] // Neural Systems and Rehabilitation Engineering, IEEE Transactions on. Sept de 2013, 5, 21, pp. 716-724. ISSN: 1534-4320 DOI: 10.1109/TNSRE.2013.2268194.

Dias N.S. [y otros] Comparison of EEG Pattern Classification Methods for Brain-Computer Interfaces [Conferencia] // Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE. 2007, pp. 2540-2543. ISSN: 1557-170X DOI: 10.1109/IEMBS. 2007.4352846.

Flores M.J., Armingol J.M. y de la Escalera A. Driver drowsiness detection system under infrared illumination for an intelligent vehicle [Publicación periódica] // Intelligent Transport Systems, IET. -December de 2011, 4, 5, pp. 241-251. ISSN: 1751-956X DOI: 10.1049/iet-its.2009.0090.

Fondo de Prevención Vial VII Encuentro Nacional de Secretarios y Autoridades de Transito // VII Encuentro Nacional de Secretarios y Autoridades de Transito. 2009.

Forsman Pia M. [y otros] Efficient driver drowsiness detection at moderate levels of drowsiness [Publicación periódica] // Accident Analysis & Prevention. 2013, 0, 50, pp. 341-350. ISSN: 0001-4575 DOI: http://dx.doi.org/10.1016/j.aap.2012.05.005.

Friedrichs F. y Yang Bin Camera-based drowsiness reference for driver state classification under real

driving conditions [Conferencia] // Intelligent Vehicles Symposium (IV), 2010 IEEE. 2010, pp. 101-106. - ISSN: 1931-0587 DOI: 10.1109/IVS.2010.5548039.

Garcés Agustina, Orosco Lorena y Laciar Eric Automatic detection of drowsiness in {EEG} records based on multimodal analysis [Publicación periódica] // Medical Engineering & Physics . 2014, 2, 36, pp. 244-249. ISSN: 1350-4533 DOI: http://dx.doi.org/10.1016/j.medengphy.2013.07.011.

Garce?s Correa A. Procesamiento de Señales cerebrales para la Detección de Somnolencia en Conductores. [Informe] : Ph.D. dissertation / Universidad Nacional de San Juan, 2011.

Garcia I. [y otros] Vision-based drowsiness detector for a realistic driving simulator [Conferencia] // Intelligent Transportation Systems (ITSC), 2010 13th International IEEE Conference on. 2010, pp.

-894. ISSN: 2153-0009 DOI: 10.1109/ITSC. 2010.5625097.

Garrett D. [y otros] Comparison of linear, nonlinear, and feature selection methods for EEG signal

classification [Publicación periódica] // Neural Systems and Rehabilitation Engineering, IEEE Transactions on. June de 2003, 2, 11, pp. 141-144. ISSN: 1534-4320 DOI: 10.1109/TNSRE.2003. 814441.

Guzmán J. J. La Actividad Cerebral // La Actividad Cerebral. 2005. 23.Hachisuka S. Human and Vehicle-Driver Drowsiness Detection by Facial Expression [Conferencia] // Biometrics and Kansei Engineering (ICBAKE), 2013 International Conference on. 2013, pp. 320-326. DOI: 10.1109/ICBAKE.2013.89.

Hong Tianyi y Qin Huabiao Drivers drowsiness detection in embedded system [Conferencia] //

Vehicular Electronics and Safety, 2007. ICVES. IEEE International Conference on. 2007, pp. 1-5. DOI:

1109/ICVES.2007.4456381.

Hosseini S.A. y Khalilzadeh M.A. Emotional Stress Recognition System Using EEG and Psychophysiological Signals: Using New Labelling Process of EEG Signals in Emotional Stress State [Conferencia] // Biomedical Engineering and Computer Science (ICBECS), 2010 International Conference on. 2010, pp. 1-6. DOI: 10.1109/ICBECS.2010.5462520.167 Sistemas de detección de somnolencia en conductores... / Garcés & Cols. Revista Ingeniería y Región. 2015;13(1):159-168

International Labour Organization Causas de accidentes laborales: Las alteraciones del sueño en los

accidentes // Causas de accidentes laborales: Las alteraciones del sueño en los accidentes. 2013.

Jimenez-Pinto J. y Torres-Torriti M. Driver alert state and fatigue detection by salient points analysis [Conferencia] // Systems, Man and Cybernetics, 2009. SMC 2009. IEEE International Conference on. 2009,pp. 455-461. ISSN: 1062-922X DOI: 10.1109/ICSMC.2009.5346760.

Jo Jaeik [y otros] Detecting driver drowsiness using feature-level fusion and user-specific classification [Publicación periódica] // Expert Systems with Applications. 2014, 4, Part 1: Vol. 41, pp. 1139-1152. ISSN: 0957-4174 DOI: http://dx.doi.org/10.1016/j.eswa.2013.07.108.

Kashtiban A.M., Razmi H. y Kozehkonan M.K. Combined LVQ neural network and multivariate

statistical method employing wavelet coefficient for EEG signal classification [Conferencia] // Mechatronics (ICM), 2011 IEEE International Conference on. 2011, pp. 809-814. DOI: 10.1109/ICMECH.2011.5971225.

Kim Dajeong [y otros] Detection of drowsiness with eyes open using EEG-based power spectrum analysis [Conferencia] // Strategic Technology (IFOST), 2012 7th International Forum on. 2012, pp. 1-4. DOI:10.1109/IFOST.2012.6357815.

Lee B.-G., Jung S.-J. y Chung W.-Y. Real-time physiological and vision monitoring of vehicle driver

for non-intrusive drowsiness detection [Publicación periódica] // Communications, IET. - November de

, 17, 5, pp. 2461-2469. ISSN: 1751-8628 DOI: 10.1049/iet-com.2010.0925. 32.Li Xin, Cui Wei y Li Changwu Research on classification method of wavelet entropy and Fuzzy Neural Networks for motor imagery EEG [Conferencia] // Modelling, Identification Control (ICMIC), 2012 Proceedings of International Conference on. 2012, pp. 478-482.

Lin Chin-Teng [y otros] A Real-Time Wireless Brain Computer Interface System for Drowsiness Detection [Publicación periódica] // Biomedical Circuits and Systems, IEEE Transactions on. - Aug

de 2010. 4, 4, pp. 214-222. ISSN: 1932-4545 DOI:10.1109/TBCAS.2010.2046415.

measures: Recent insights and future challenges [Publicación periódica] // Journal of Safety Research . - 2009, 4, 40, pp. 239-245. ISSN: 0022-4375 DOI: http://dx.doi.org/10.1016/j.jsr.2009.04.005.

Maglione A. [y otros] Evaluation of the workload and drowsiness during car driving by using high

resolution EEG activity and neurophysiologic indices [Conferencia] // Engineering in Medicine and Biology Society (EMBC), 2014 36th Annual International Conference of the IEEE. 2014, pp. 6238-6241. ISSN:1557-170X DOI: 10.1109/EMBC.2014. 6945054.

Masala G.L. y Grosso E. Real time detection of driver attention: Emerging solutions based on robust iconicclassifiers and dictionary of poses [Publicación periódica] // Transportation Research Part C: Emerging Technologies. 2014, 0, 49, pp. 32-42. ISSN: 0968-090X DOI: http://dx.doi.org/10.1016/j.trc.2014.10.005.

MCKEOWN MARTIN J. [y otros] A new method for detecting state changes in the EEG: exploratory

application to sleep data [Publicación periódica] // Journal of Sleep Research. 1998, 7, pp. 48-56.

MIN MERVYN YEO VEE AN EEG BASED STUDYOF UNINTENTIONAL SLEEP ONSET [Informe]: Ph.D. dissertation / NATIONAL UNIVERSITY OF SINGAPORE. 2007.

Phothisonothai M. y Nakagawa Masahiro EEG signal classification method based on fractal features and neural network [Conferencia] // Engineering in Medicine and Biology Society, 2008. EMBS 2008. 30th Annual International Conference of the IEEE. 2008, pp. 3880-3883. ISSN: 1557-170X DOI: 10.1109/IEMBS.2008.4650057.

Picot A., Charbonnier Sylvie y Caplier A. On-Line Detection of Drowsiness Using Brain and Visual

Information [Publicación periódica] // Systems, Manand Cybernetics, Part A: Systems and Humans, IEEE Transactions on. - May de 2012, 3, 42, pp. 764-775. ISSN: 1083-4427 DOI: 10.1109/TSMCA.2011.2164242.

Powell Nelson B. y Chau Jason K.M. Sleepy Driving [Publicación periódica] // Medical Clinics of North America. 2010, 3, 94, pp. 531-540. Sleep Medicine. ISSN: 0025-7125 DOI: http://dx.doi.org/10.1016/j.mcna.2010.02.002.168

Principe J.C., Gala S.K. y Chang T.G. Sleep staging automaton based on the theory of evidence [Publicación periódica] // Biomedical Engineering, IEEE Transactions on. May de 1989, 5, 36, pp. 503-509. ISSN: 0018-9294 DOI: 10.1109/10.24251.

Sabet M. [y otros] A new system for driver drowsiness and distraction detection [Conferencia] //

Electrical Engineering (ICEE), 2012 20th Iranian Conference on. 2012, pp. 1247-1251. DOI: 10.1109/

IranianCEE.2012.6292547.

Shaout A., Colella D. y Awad S. Advanced Driver Assistance Systems - Past, present and future [Conferencia] // Computer Engineering Conference (ICENCO), 2011 Seventh International. 2011, pp.

-82. DOI: 10.1109/ICENCO.2011.6153935.

Sun Shiliang y Zhou Jin A review of adaptive feature extraction and classification methods for EEG-based brain-computer interfaces [Conferencia] // Neural Networks (IJCNN), 2014 International Joint

Conference on. 2014, pp. 1746-1753. DOI: 10.1109/IJCNN.2014.6889525.

Universidad Nacional de Colombia Trastornos del Sueño // Trastornos del Sueño. Bogotá: Lecciones

Medicina, 2005. Vol. Capítulo 5.

Villar Shirley Cordova, Oviedo Willian A. Perez y Gonzalez Avid Román Implementation of EEG signal processing methods for communication and control application [Publicación periódica] // Revista

ECIPerú. October de 2013, 1, 10, pp. 24-33.

Wang Boyu [y otros] Comparison of different classification methods for EEG-based brain computer interfaces: A case study [Conferencia] // Information and Automation, 2009. ICIA’09. International Conference on. 2009, pp. 1416-1421. DOI: 10.1109/ICINFA.2009.5205138.

Wang Zhihua [y otros] Study of signal processing system for Electroencephalogram based on TMS320LF2407 [Conferencia] // Automation Congress, 2008. WAC 2008. World. 2008, pp. 1-4.

Wilson B.J. y Bracewell T.D. Alertness monitor using neural networks for EEG analysis [Conferencia] //Neural Networks for Signal Processing X, 2000. Proceedings of the 2000 IEEE Signal Processing

Society Workshop. 2000, 2, pp. 814-820. ISSN:1089-3555 DOI: 10.1109/NNSP.2000.890161.

World Health Organization Top 10 de las causas de muerte // Top 10 de las causas de muerte.2012.

Yang Ji Hyun [y otros] Detection of Driver Fatigue Caused by Sleep Deprivation [Publicación periódica]// Systems, Man and Cybernetics, Part A:Systems and Humans, IEEE Transactions on. - July

de 2009, 4, 39, pp. 694-705. ISSN: 1083-4427 DOI:10.1109/TSMCA.2009.2018634.

Yeo Mervyn V.M. [y otros] Can SVM be used for automatic EEG detection of drowsiness during cardriving? [Publicación periódica] // Safety Science.2009, 1, 47, pp. 115-124. ISSN: 0925-7535 DOI:

http://dx.doi.org/10.1016/j.ssci.2008.01.007.

Zhao Chunlin [y otros] Electroencephalogram and electrocardiograph assessment of mental fatigue in a driving simulator [Publicación periódica] // Accident Analysis & Prevention. 2012, 0, 45, pp. 83-90. ISSN: 0001-4575 DOI: http://dx.doi.org/10.1016/j.aap.2011.11.019.