Nội dung được dịch bởi AI, chỉ mang tính chất tham khảo
Phương pháp phát hiện và loại bỏ các hiện tượng gây nhiễu từ mắt trong các tín hiệu EEG trong hệ thống cảnh báo lái xe buồn ngủ: Một khảo sát
Tóm tắt
Trong thập kỷ qua, tình trạng buồn ngủ khi lái xe đã được xác định là một yếu tố chính gây ra nhiều vụ tai nạn giao thông chết người trên toàn thế giới. Vấn đề phổ biến này đã gây ra thiệt hại nghiêm trọng về sinh mạng, thương tích, hư hỏng tài sản và thiệt hại kinh tế ở nhiều khu vực trên thế giới. Chính vì vậy, đã có nhiều nỗ lực để giới thiệu các hệ thống phát hiện buồn ngủ của tài xế nhằm giảm thiểu và ngăn ngừa tai nạn giao thông tại nhiều thành phố trên thế giới. Trong số các hệ thống hỗ trợ lái xe hiện có, hệ thống dựa trên việc đo tín hiệu EEG là phổ biến và có liên quan nhất. Tuy nhiên, tín hiệu EEG dễ bị ảnh hưởng bởi nhiều loại nhiễu xuất phát từ các nguồn khác ngoài não, chẳng hạn như hoạt động cơ bắp (EMG), hoạt động tim (ECG) và hoạt động mắt (EOG). Trong số đó, hiện tượng gây nhiễu từ mắt là một trong những nguồn gây nhiễu quan trọng nhất. Trong bài báo này, chúng tôi trình bày một cái nhìn sâu sắc về các kỹ thuật được sử dụng để phát hiện và loại bỏ các hiện tượng gây nhiễu từ mắt trong các ghi nhận EEG cho tất cả các ứng dụng cảnh báo buồn ngủ dựa trên EEG. Đầu tiên, chúng tôi giới thiệu tổng quan về một số loại nhiễu quan trọng có thể quan sát trong tín hiệu EEG và nghiên cứu tác động của chúng đối với các ứng dụng phát hiện buồn ngủ. Tiếp theo, chúng tôi xem xét nhiều phương pháp loại bỏ nhiễu, phân loại và so sánh chúng dựa trên khả năng loại bỏ hiện tượng EOG. Cuối cùng, chúng tôi cung cấp một ý tưởng đổi mới dựa trên đám mây IoT, có thể là bước tiếp theo cho việc lái xe an toàn, để cảnh báo tài xế khi họ đang buồn ngủ.
Từ khóa
Tài liệu tham khảo
Akerstedt T, Basseti C, Cirignotta F, Garcia-Borreguero D, Gonçalves M, Horne J, Léger D, ParTinen M, Penzel T, Philip P, Verster J-C (2013) La somnolence au volant -Livre Blanc-
Aniket M, Arpit L, Krupa BN (2015) Removal of ocular artifacts in EEG signals using adapted wavelet and adaptive filtering. In: The proceedings of the international conference for innovation in biomedical engineering and life sciences, IFMBE proc, vol 56, pp 62–67
Arnin J, Anopas D, Horapong M, Triponyuwasi P, Yamsa-ard T, Iampetch S, Wongsawat Y (2013) Wireless-based portable EEG-EOG monitoring for real time drowsiness detection. In: Proceedings of 35th Annual international conference of the IEEE EMBS, pp 4977–4980
Bansal D, Mahajan R (2019) EEG-based brain-computer interfaces: Cognitive analysis and control applications, 1st Edition ISBN: 9780128146873
citation_journal_title=J Netw Comput Appl; citation_title=VEACON: A vehicular accident ontology designed to improve safety on the roads; citation_author=J Barrachina, P Garrido, M Fogue, FJ Martinez, JC Cano, CT Calafate, P Manzoni; citation_volume=35; citation_issue=6; citation_publication_date=2012; citation_pages=1891-1900; citation_doi=10.1016/j.jnca.2012.07.013; citation_id=CR5
Behera S, Mohanty MN (2018) A statistical approach for ocular artifact removal in brain signals. In: The proceedings of the 2nd International Conference on Data Science and Business Analytics (ICDSBA), Changsha, pp 500–503
citation_title=Integration of cloud computing and internet of things: A survey. future generation computer systems, vol 56; citation_publication_date=2016; citation_id=CR7; citation_author=A Botta; citation_author=W Donato; citation_author=V Persico; citation_author=A Pescap; citation_publisher=Elsevier
citation_journal_title=Médecine du Sommeil; citation_title=Consequences of sleep loss in adolescence; citation_author=A Brion; citation_volume=8; citation_issue=4; citation_publication_date=2011; citation_pages=145-151; citation_doi=10.1016/j.msom.2011.09.002; citation_id=CR8
citation_journal_title=Expert Syst Appl; citation_title=A novel system for automatic removal of ocular artefacts in EEG by using outlier detection methods and independent component analysis; citation_author=S Çinar, N Acir; citation_volume=68; citation_issue=C; citation_publication_date=2017; citation_pages=36-44; citation_doi=10.1016/j.eswa.2016.10.009; citation_id=CR9
citation_journal_title=IEEE Consum Electron Mag; citation_title=Detecting driver drowsiness: a survey of system designs and technology; citation_author=MI Chacon-Murguia, C Prieto-Resendiz; citation_volume=4; citation_issue=4; citation_publication_date=2015; citation_pages=107-119; citation_doi=10.1109/MCE.2015.2463373; citation_id=CR10
citation_journal_title=IEEE Consum Electron Mag; citation_title=Detecting driver drowsiness: a survey of system designs and technology; citation_author=MI Chacon-Murguia, C Prieto-Resendiz; citation_volume=4; citation_issue=4; citation_publication_date=2015; citation_pages=107-119; citation_doi=10.1109/MCE.2015.2463373; citation_id=CR11
citation_journal_title=IEEE Trans Intell Transp Syst; citation_title=Onboard measurement and warning module for irregular vehicle behavior; citation_author=TH Chang, CS Hsu, C Wang, LK Yang; citation_volume=9; citation_issue=3; citation_publication_date=2008; citation_pages=501-513; citation_doi=10.1109/TITS.2008.928243; citation_id=CR12
citation_title=Driver drowsiness detection: Systems and solutions. Part of the Springer Briefs in Computer Science book series (BRIEFS COMPUTER); citation_publication_date=2014; citation_id=CR13; citation_author=A Čolić; citation_author=O Marques; citation_author=B Furht; citation_publisher=Springer
citation_journal_title=Med Eng Phys; citation_title=Automatic detection of drowsiness in EEG records based on multimodal analysis; citation_author=AG Correa, L Orosco, E Laciar; citation_volume=36; citation_issue=2; citation_publication_date=2014; citation_pages=224-249; citation_id=CR14
citation_journal_title=J Netw Comput Appl; citation_title=An inverse Bayesian scheme for the denoising of ECG signals; citation_author=S Cuomo, R Farina, F Piccialli; citation_volume=115; citation_publication_date=2018; citation_pages=48-58; citation_doi=10.1016/j.jnca.2018.04.016; citation_id=CR15
citation_journal_title=Inter J Comput Sci Technol; citation_title=Anomaly detection using principal component analysis; citation_author=AS Deepthi, KV Rao; citation_volume=5; citation_issue=4; citation_publication_date=2014; citation_pages=124-126; citation_id=CR16
citation_journal_title=Inter J Comput Appl (0975–8887); citation_title=Survey on driver’s drowsiness detection system; citation_author=O Dharmadhikari, R Bhor, P Mahajan, HV Kumbhar; citation_volume=132; citation_issue=5; citation_publication_date=2015; citation_pages=16-19; citation_id=CR17
Di-Flumeri G, Arico P, Borghini G, Colosimo A, Babiloni F (2016) A new regression-based method for the eye blinks artifacts correction in the EEG signal, without using any EOG channel. In: Proceedings of the 38th annual international conference of the IEEE engineering in medicine and biology society (EMBC), pp 3187–3190
Electromyograms (n.d.) (2003) Miller-Keane Encyclopedia and Dictionary of Medicine, Nursing, and Allied Health, Seventh Edition. Retrieved July 13 2019 from
https://medical-dictionary.thefreedictionary.com/electromyograms
Accessed 13 July 2019
citation_journal_title=Neural Network World; citation_title=Detection of different levels of vigilance by EEG pseudo spectra; citation_author=J Faber; citation_volume=14; citation_issue=3–4; citation_publication_date=2004; citation_pages=285-290; citation_id=CR20
citation_journal_title=Clin Neurophysiol; citation_title=EMG And EOG artifacts in brain computer interface systems: A survey; citation_author=M Fatourechi, A Bashashati, RK Ward, GE Birch; citation_volume=118; citation_issue=3; citation_publication_date=2007; citation_pages=480-494; citation_doi=10.1016/j.clinph.2006.10.019; citation_id=CR21
citation_journal_title=Electroencephalogr Clin Neurophysiol; citation_title=Clinical applications of spectral analysis and extraction of features from electroencephalograms with slow waves in adult patients; citation_author=J Gotman, DR Skuce, CJ Thompson, P Gloor, JR Ives, WF Ray; citation_volume=35; citation_issue=3; citation_publication_date=1973; citation_pages=225-235; citation_doi=10.1016/0013-4694(73)90233-2; citation_id=CR22
citation_journal_title=Electroencephalogr Clin Neurophysiol; citation_title=A new method for off-line removal of ocular artifact; citation_author=G Gratton, MGH Coles, E Donchin; citation_volume=55; citation_issue=4; citation_publication_date=1983; citation_pages=468-484; citation_doi=10.1016/0013-4694(83)90135-9; citation_id=CR23
citation_journal_title=IET Signal Process; citation_title=Automatic removal of ocular artefacts using adaptive filtering and independent component analysis for electroencephalogram data; citation_author=C Guerrero-Mosquera, A Navia-Vazquez; citation_volume=6; citation_issue=2; citation_publication_date=2012; citation_pages=99-106; citation_doi=10.1049/iet-spr.2010.0135; citation_id=CR24
citation_journal_title=Med Biol Eng Comput; citation_title=Removal of ocular artifacts from electroencephalogram by adaptive filtering; citation_author=P He, G Wilson, C Russel; citation_volume=42; citation_issue=3; citation_publication_date=2004; citation_pages=407-412; citation_doi=10.1007/BF02344717; citation_id=CR25
citation_journal_title=IET Intell Transp Syst; citation_title=Driver fatigue detection from electroencephalogram spectrum after electrooculography artefact removal; citation_author=S Hu, G Zheng, B Peters; citation_volume=7; citation_issue=1; citation_publication_date=2013; citation_pages=105-113; citation_doi=10.1049/iet-its.2012.0045; citation_id=CR26
citation_journal_title=Proc Math Phys Eng Sci; citation_title=The empirical mode decomposition and the hilbert spectrum for nonlinear and non-stationary time series analysis; citation_author=NE Huang, Z Shen, SR Long, MC Wu, HH Shih, Q Zheng, NC Yen, CC Tung, HH Liu; citation_volume=454; citation_issue=1971; citation_publication_date=1998; citation_pages=903-995; citation_doi=10.1098/rspa.1998.0193; citation_id=CR27
Inuso G, la Foresta F, Mammone N, Morabito FC (2007) Brain activity investigation by EEG processing: Wavelet analysis, kurtosis and renyi’s entropy for artifact detection. International Conference on Information Acquisition, pp 195–200
citation_journal_title=Clin Neurophysiol; citation_title=Methods for artifact detection and removal from scalp EEG: A review; citation_author=MdK Islam, A Rastegarnia, Z Yang; citation_volume=46; citation_issue=4–5; citation_publication_date=2016; citation_pages=287-305; citation_doi=10.1016/j.neucli.2016.07.002; citation_id=CR29
citation_journal_title=Neurocomputing; citation_title=Artifacts removal in EEG signal using a new neural network enhanced adaptive filter; citation_author=A Jafarifarmand, MA Badamchizadeh; citation_volume=103; citation_issue=1; citation_publication_date=2013; citation_pages=222-231; citation_doi=10.1016/j.neucom.2012.09.024; citation_id=CR30
citation_journal_title=Sensors; citation_title=Removal of artifacts from EEG signals: A Review; citation_author=X Jiang, GB Bian, Z Tian; citation_volume=19; citation_issue=987; citation_publication_date=2019; citation_pages=1-18; citation_id=CR31
Jirayucharoensak S, Israsena P (2013) Automatic removal of EEG artifacts using ICA and lifting wavelet transform. In: Proceedings of International computer science and engineering conference, pp 136– 139
citation_journal_title=IEEE Trans Intell Transp Syst; citation_title=Driver behavior analysis for safe driving: A survey; citation_author=S Kaplan, MA Guvensan, AG Yavuz, Y Karalurt; citation_volume=16; citation_issue=6; citation_publication_date=2015; citation_pages=3017-3032; citation_doi=10.1109/TITS.2015.2462084; citation_id=CR33
Kavitha PT, Lau CT, Premkumar AB, filtering AB (2007) Modified ocular artifact removal technique from EEG by adaptive filtering. In: Proceedings of the 6th International conference on information communications & signal processing, pp 1–5
citation_journal_title=IEEE J Transl Eng Health Med; citation_title=Comparative study of wavelet-based unsupervised ocular artifact removal techniques for single-channel EEG data; citation_author=S Khatun, R Mahajan, BI Morshed; citation_volume=4; citation_publication_date=2016; citation_pages=1-8; citation_doi=10.1109/JTEHM.2016.2544298; citation_id=CR35
citation_journal_title=Inter J Adv Res Comput Commun Eng; citation_title=A survey on different noise removal techniques of EEG signals; citation_author=P Khatwani, A Tiwari; citation_volume=2; citation_issue=2; citation_publication_date=2013; citation_pages=1091-1095; citation_id=CR36
Knipling RR, Wang JS (1995) Revised estimates of the US drowsy driver crash problem size based on general estimates system case reviews. In: Annual proceedings of the association for the advancement of automotive medicine, vol 39, pp 451–466
Kozielski S, Mrozek D, Kasprowski P, Małysiak-Mrozek B, Kostrzewa D (2016) Beyond databases, architectures and structures: Advanced technologies for data mining and knowledge discovery. In: The proceedings of the 12th international conference: BDAS
citation_journal_title=Inter J Open Problems Comput Sci Math; citation_title=Removal of ocular artifacts in the EEG through wavelet transform without using an EOG reference channel; citation_author=PS Kumar, R Arumuganathan, K Sivakumar, C Vimal; citation_volume=1; citation_issue=3; citation_publication_date=2008; citation_pages=189-200; citation_id=CR39
citation_journal_title=J Netw Comput Appl; citation_title=A bio-signal based framework to secure mobile devices; citation_author=P Kumar, R Saini, PP Roy, DP Dogra; citation_volume=89; citation_publication_date=2017; citation_pages=62-71; citation_doi=10.1016/j.jnca.2017.02.011; citation_id=CR40
citation_journal_title=Inter J Adv Res Comput Sci Software Eng; citation_title=Survey on EEG signal processing methods; citation_author=MR Lakshmi, TV Prasad, VC rakash; citation_volume=4; citation_issue=1; citation_publication_date=2014; citation_pages=84-91; citation_id=CR41
Lee KJ, Park C, Lee B (2015) Elimination of ECG artifacts from a single-channel EEG using sparse derivative method. In: The proceedings of the international conference on systems, man, and cybernetics, pp 2384–2389
citation_journal_title=IEEE Trans Circuits Syst I Regul Pap; citation_title=EEG-Based drowsiness estimation for safety driving using independent component analysis; citation_author=CT Lin, RC Wu, SF Liang, WH Chao, YJ Chen, TP Jung; citation_volume=52; citation_issue=12; citation_publication_date=2005; citation_pages=2726-2738; citation_doi=10.1109/TCSI.2005.857555; citation_id=CR43
citation_journal_title=IEEE J Biomed Health Inform; citation_title=Unsupervised eye blink artifact denoising of EEG data with modified multiscale sample entropy, kurtosis and wavelet-ICA; citation_author=R Mahajan, BI Morshed; citation_volume=19; citation_issue=1; citation_publication_date=2015; citation_pages=158-165; citation_doi=10.1109/JBHI.2014.2333010; citation_id=CR44
citation_journal_title=ACM Trans Embed Comput Syst; citation_title=Autonomous OA removal in real-time from single channel EEG data on a wearable device using a hybrid algebraic-wavelet algorithm; citation_author=CA Majmudar, BI Morshed; citation_volume=16; citation_issue=1; citation_publication_date=2016; citation_pages=1-16; citation_doi=10.1145/2983629; citation_id=CR45
citation_journal_title=IEEE Access; citation_title=Identification and removal of physiological artifacts from electroencephalogram aignals: A review; citation_author=MMN Mannan, MA Kamran, MY Jeong; citation_volume=6; citation_publication_date=2018; citation_pages=30630-30652; citation_doi=10.1109/ACCESS.2018.2842082; citation_id=CR46
citation_journal_title=Inter J Adv Res Comput Sci Manag Stud; citation_title=A survey: fundamental of EEG; citation_author=S Mantri, V Dukare, S Yeole; citation_volume=1; citation_issue=4; citation_publication_date=2013; citation_pages=83-89; citation_id=CR47
Minhas AA, Jabbar S, Farhan M, ul Islam MN (2019) Smart methodology for safe life on roads with active drivers based on real-time risk and behavioral monitoring. Journal of Ambient Intelligence and Humanized Computing
Mohammedi M, Omar M, Bouabdallah A (2018) Automatic removal of ocular artifacts in EEG signals for driver’s drowsiness detection: A survey. In: The proceedings of the 7th IEEE international conference on smart communications in network technologies (SaCoNeT), pp 188–193
Morales JM, Di Stasi LL, Díaz-Piedra C, Morillas C, Romero S (2015) Real-time monitoring of biomedical signals to improve road safety. In: Rojas, I., Joya, G., Catala, A. (eds) Advances in computational intelligence. IWANN 2015. Lecture notes in computer science, vol 9094. Springer, Cham, pp 89–97
citation_journal_title=Investig Ophthalmol; citation_title=Accuracy and precision of electrooculographic recording; citation_author=AW North; citation_volume=4; citation_issue=3; citation_publication_date=1965; citation_pages=343-348; citation_id=CR51
Ocvirk T (2020) The association between sleep and physical activity in hypertensive individuals, Master’s Thesis, Department of Biology of Physical Activity University of Jyväskylä
Pham T, Ma W, Tran D, Nguyen P, Phung D (2013) A study on the feasibility of using EEG signals for authentication purpose. Chapter: Neural information processing, vol 8227 of the series Lecture Notes in Computer Science, pp 562–569
Picot A, Charbonnier S, Caplier A (2009) Monitoring drowsiness on-line using a single encephalographic channel, Recent Advances in Biomedical Engineering, Rijeka, Croatia: IN-TECH, pp 145–164
citation_journal_title=Accid Anal Prev; citation_title=Evaluating the removal composition of common artefacts in EEG signals for driving behaviour analysis; citation_author=G Qi, S Zhao, A(Avi) Ceder, W Guan, X Yan; citation_volume=159; citation_publication_date=2021; citation_pages=1-12; citation_doi=10.1016/j.aap.2021.106223; citation_id=CR55
citation_journal_title=Neural Regen Res; citation_title=Rabiul Artifact suppression and analysis of brain activities with electroencephalography signals; citation_author=Md Rashed-Al-Mahfuz, Md Islam, K Hirose, MdkI Molla; citation_volume=8; citation_issue=16; citation_publication_date=2013; citation_pages=1500-1513; citation_id=CR56
Rau PS (2005) Drowsy driver detection and warning system for commercial vehicle drivers: Field operational test design, data analyses, and progress. In: Proceedings of 19th International conference on enhanced safety of vehicles Washington, DC, pp 1–7
citation_journal_title=IEEE Int Things J; citation_title=Middleware for internet of things: A survey; citation_author=MA Razzaque, M Milojevic-Jevric, A Palade, S Clarke; citation_volume=3; citation_issue=1; citation_publication_date=2016; citation_pages=70-95; citation_doi=10.1109/JIOT.2015.2498900; citation_id=CR58
citation_journal_title=Biol Proced Online; citation_title=Techniques of EMG signal analysis: detection, processing, classification and applications; citation_author=MBI Reaz, MS Hussain, F Mohd-Yasin; citation_volume=8; citation_issue=1; citation_publication_date=2006; citation_pages=11-35; citation_doi=10.1251/bpo115; citation_id=CR59
citation_journal_title=Int J Multimed Ubiquitous Eng; citation_title=A survey on artifacts detection techniques for electroencephalography (EEG) Signals; citation_author=V Roy, S Shukla; citation_volume=10; citation_issue=3; citation_publication_date=2015; citation_pages=425-442; citation_doi=10.14257/ijmue.2015.10.3.39; citation_id=CR60
citation_journal_title=IEEE Trans Intell Transp Syst; citation_title=Detecting driver sleepiness using optimized nonlinear combinations of sleepiness indicators; citation_author=D Sandberg, T Ȧkerstedt, A Anund, G Kecklund, M Wahde; citation_volume=12; citation_issue=1; citation_publication_date=2011; citation_pages=97-108; citation_doi=10.1109/TITS.2010.2077281; citation_id=CR61
Sarhan A (2019) Cloud-based IoT platform: Challenges and applied solutions. Chapter 6 IGI Global, pp 116–147
citation_journal_title=Comput Math Methods Med; citation_title=An EEG database and its initial benchmark emotion classification performance; citation_author=A Seal, PPN Reddy, P Chaithanya, A Meghana, K Jahnavi, O Krejcar, R Hudak; citation_volume=2020; citation_issue=8303465; citation_publication_date=2020; citation_pages=1-14; citation_doi=10.1155/2020/8303465; citation_id=CR63
citation_journal_title=Inter J Adv Res Comput Commun Eng; citation_title=Safety device for drowsy driving using IoT; citation_author=T Sehgal, S Maindalkar, S More; citation_volume=5; citation_issue=9; citation_publication_date=2016; citation_pages=186-188; citation_id=CR64
citation_journal_title=Int J Adv Res Electron Commun Eng; citation_title=Iot based driver alerteness and health monitoring system; citation_author=T Shwetha, JP Rao, B Sreenivasu; citation_volume=6; citation_issue=10; citation_publication_date=2017; citation_pages=1093-1099; citation_id=CR65
Singh D, Tripathi G, Jara AJ (2014) A survey of internet-of-things: Future vision, architecture, challenges and services. In: Proceedings of IEEE world forum on internet of things, pp 287–292
citation_journal_title=J Med Syst; citation_title=EEG Signal analysis: a survey; citation_author=DP Subha, PK Joseph, RU Acharya, CM Lim; citation_volume=34; citation_issue=2; citation_publication_date=2010; citation_pages=195-212; citation_doi=10.1007/s10916-008-9231-z; citation_id=CR67
Statistics related to drowsy driver crashes. <
http://www.americanindian.net/sleepstats.html
>. Accessed 26 April 2019
Sundararajan A, Pons A, Sarwat AI (2015) A generic framework for EEG-based biometric authentication. In: Proceedings of the 12th International conference on information technology - New generations, pp 139–144
citation_journal_title=IEEE Trans Biomed Eng; citation_title=The use of ensemble empirical mode decomposition with canonical correlation analysis as a novel artifact removal technique; citation_author=KT Sweeney, SF McLoone, TE Ward; citation_volume=60; citation_issue=1; citation_publication_date=2013; citation_pages=97-105; citation_doi=10.1109/TBME.2012.2225427; citation_id=CR70
citation_journal_title=Meas Sci Rev; citation_title=Fundamentals of EEG measurement; citation_author=M Teplan; citation_volume=2; citation_issue=2; citation_publication_date=2002; citation_pages=1-11; citation_id=CR71
The royal society for the prevention of accidents Driver fatigue and road accidents: A literature review and position paper. Technical report, Birmingham, U.K, pp 1–24
Tiganj Z, Mboup M, Pouzat C, Lotfi B (2010) An algebraic method for eye blink artifacts detection in single channel EEG recordings. In: Proceedings of the 17th international conference on biomagnetism advances in biomagnetism–BIOMAG 2010, pp 175–178
Tijerina L, Gleckler M, Stoltzfus D, Johnston S, Goodman MJ, Wierwille WW (1999) A preliminary assessment of algorithms for drowsy and inattentive driver detection on the road. National Highway Trafic Safety Administration, Report Number DOT HS 808 (TBD)
Tuncer T, Dogan S, Ertam F, Subasi A (2020) A dynamic center and multi threshold point based stable feature extraction network for driver fatigue detection utilizing EEG signals. Cognitive Neurodynamics, pp 1–15
citation_journal_title=Inter J Adv Res Comput Eng Technol; citation_title=Road accidents prevention system using driver’s drowsiness detection; citation_author=G Turan, S Gupta; citation_volume=2; citation_issue=11; citation_publication_date=2013; citation_pages=2981-2983; citation_id=CR76
Ueno H, Kaneda M, Tsukino M (1994) Development of drowsiness detection system. In: Proceedings of VNIS’94 - 1994 vehicle navigation and information systems conference, pp 15–20, DOI
https://doi.org/10.1109/VNIS.1994.396873
, (to appear in print)
citation_journal_title=Inter J Sci Eng Res; citation_title=Real time driver’s srowsiness detection system based on eye conditions; citation_author=A Ullah, S Ahmed, L Siddiqui, N Faisal; citation_volume=6; citation_issue=3; citation_publication_date=2015; citation_pages=125-131; citation_id=CR78
Upadhyay R, Padhy PK, Kankar PK (2015) Ocular artifact removal from EEG signals using discrete orthonormal stockwell transform. In: Proceedings of the Annual IEEE India Conference (INDICON), pp 1–5, DOI
https://doi.org/10.1109/INDICON.2015.7443617
, (to appear in print)
Vanlaar W, Simpson HM, Mayhew D, Robertson R (2007) Fatigued and drowsy driving: Attitudes, concerns and practices of ontario drivers. Technical report, Traffic Injury Research Foundation, pp 1–32
citation_journal_title=Psychophysiology; citation_title=Correction of EOG artifacts in event-related potentials of the EEG: Aspects of reliability and validity; citation_author=R Verleger, T Gasser, J Möcks; citation_volume=19; citation_issue=4; citation_publication_date=1982; citation_pages=472-480; citation_doi=10.1111/j.1469-8986.1982.tb02509.x; citation_id=CR81
citation_journal_title=IEE Proc-Sci, Meas Technol; citation_title=Quantitative evaluation of techniques for ocular artefact filtering of EEG waveforms; citation_author=L Vigon, MR Saatchi, JEW Mayhew, R Fernandes; citation_volume=147; citation_issue=5; citation_publication_date=2000; citation_pages=219-228; citation_doi=10.1049/ip-smt:20000475; citation_id=CR82
citation_journal_title=Cogn Neurodyn; citation_title=A novel real-time driving fatigue detection system based on wireless dry EEG; citation_author=H Wang, A Dragomir, NI Abbasi, J Li, NV Thakor, A Bezerianos; citation_volume=12; citation_issue=4; citation_publication_date=2018; citation_pages=365-376; citation_doi=10.1007/s11571-018-9481-5; citation_id=CR83
citation_journal_title=IEEE Access; citation_title=Driving fatigue classification based on fusion entropy analysis combining EOG and EEG; citation_author=H Wang, C Wu, T Li, Y He, P Chen, A Bezerianos; citation_volume=7; citation_publication_date=2019; citation_pages=1-12; citation_id=CR84
Wang Q, Yang J, Ren M, Zheng Y (2006) Driver fatigue detection: a survey. In: Proceedings of the 6th World congress on intelligent control and automation, pp 8587–8591
citation_journal_title=Biol Psychol; citation_title=The removal of the eye-movement artifact from the EEG by regression analysis in the frequency domain; citation_author=JC Woestenburg, MN Verbaten, JL Slangen; citation_volume=16; citation_issue=1–2; citation_publication_date=1983; citation_pages=127-147; citation_doi=10.1016/0301-0511(83)90059-5; citation_id=CR86
citation_journal_title=Adv Adapt Data Anal; citation_title=Ensemble empirical mode decomposition: a noise-assisted data analysis method; citation_author=Z Wu, NE Huang; citation_volume=1; citation_issue=1; citation_publication_date=2009; citation_pages=1-41; citation_doi=10.1142/S1793536909000047; citation_id=CR87
Zikov T, Bibian S, Dumont GA, Huzmezan M, Ries CR (2002) A wavelet based de-noising technique for ocular artifact correction of the electroencephalogram. In: Proceedings of the IEEE engineering in medicine and biology 24th Annual conference and the fall meeting of the biomedical engineering society, pp 98–105
Zou S, Qiu T, Huang P, Bai X, Liu C (2020) Constructing multi-scale entropy based on the empirical mode decomposition(EMD) and its application in recognizing driving fatigue, Journal of Neuroscience Methods, pp 1–16
