Analysis on Fatigue Recognition System Using Facial Features and HRV

 
 
 
  • Abstract
  • Keywords
  • References
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  • Abstract


    Observing the driver's state of cognizance and weakness is totally important to diminish the amount of road accidents. A simple approach cognitive approach for inspection of driver safety levels by combining facial features and Heart rate Variability (HRV) is discussed.Fatigue detection is performed through Simulation that involves face detection, face localization, eye detection, thresholding and eye blink detection using Matlab and OpenCV. Heart rate was analysed using Signal Acquisition, Filtering, R-R Peak Interval Extraction and heart rate calculation. The simulation was performed using LabVIEW. A simple modelwas analysed using sensors wrapped into steering wheel and from it if the measured pulse rate is lesser than 65 the system detects it as low heart rate which corresponds to drowsiness detection.

     

     



  • Keywords


    Biomedical computing, Electrocardiogram, Fatigue, Medical information systems, Matlab, LabVIEW.

  • References


      [1] Driver fitness and monitoring branch, keeping drivers safe and mobile, http://www.transportation.alberta.ca/Content/docType47/Production/drvfitness.pdf

      [2] T. Morris, P. Blenkhorn and F. Zaidi, Blink detection for real-time eye tracking, Journal of Network and Computer Applications (2002), 129-143.

      [3] Hossein Seifoory, DavoodTaherkhani, BehnsmArzhang, Zahra Eftekhari, Hamid Memari,An Accurate Morphological Drowsy Detection, International Proceedings of Computer Science and Technology(2011),51-54.

      [4] Youn Sung Kima, Hyun Jae Baekb, Jung Soo Kima, Haet Bit Leea, Jong Min Choia, Kwang ,Suk Parkc, Helmet based physiological Monitoring System, European Journal of Applied Physiology (2009), 365-372.

      [5]Y.Yang, M.McDonald, P.Zheng, Can drivers' eye movements be used to monitor their performance? a case study, IET journal of Intelligent Transport Systems (2012),444 – 452

      [6] Lin, Yingzi ,Leng, Hongjie; Yang, G.; Cai, Hua , An Intelligent Noninvasive Sensor for Driver Pulse Wave Measurement, IEEE Sensors Journal (2007), 790–799.

      [7] Antoine Picot, Sylvie Charbonnier and Alice Caplier (2010), Drowsiness detection based on visual signs: blinking analysis based on high frame rate video, IEEE International Instrumentation and Measurement Technology Conference (2010).

      [8]Taner Danisman, Ian Marius Bilasco, Chabane Djeraba, Nacim Ihaddadene, Drowsy Driver Detection System Using Eye Blink Patterns, proceedings of IEEE International conference on machine and web intelligence(2010),230-233,.

      [9] Ilkwon Park, Jung-Ho Ahn, Hyeran Byun, Efficient Measurement of Eye Blinking Under Various Illumination Conditions For Drowsiness Detection Systems, IEEE 18th International conference on Pattern recognition (2006), 383-386

      [10] XingliangXion ,Lifang Deng, Yan Zhang, Longcong Chen, Objective Evaluation of Driver Fatigue by Using Spontaneous Pupillary Fluctuation, proceedings of IEEE 5th International Conference on Bioinformatics and Biomedical Engineering(2011), 1-4

      [11] Mingheng Zhang, Linhui L, Lie Guo, Yibing Zhao; Study on vision monitoring techniques of driver's face orientation, Proceedings of IEEE International Conference on Intelligent Control and Information Processing (2010), 297 – 301

      [12] Devi, Mandalapu Sarada, Bajaj, R.Preeti, Driver Fatigue Detection Based on Eye Tracking, Proceedings of First International Conference on Emerging Trends in Engineering and Technology (2008), 649 – 652.

      [13] Chien-Zhi Ou, Chiao-Tung Univ., Hsinchu, Taiwan. Etal, Brain Computer Interface-based Smart Environmental Control System, IEEE Eighth International Conference on Intelligent Information Hiding and Multimedia Signal Processing(2012), 281-284

      [14] Lee, Boon-Giin , Chung, Wan-Young Young , Driver Alertness Monitoring Using Fusion of Facial Features and Bio-Signals, IEEE Sensors Journal(2012), 2416 – 2422.

      [15] T.Danisman, Bilasco, C. Djeraba, N.Ihaddadene, Drowsy driver detection system using eye blink patterns”, Proceedings of IEEE International conference on Machine and Web Intelligence (ICMWI), pp: 230 – 233, 2010.

      [16] Lin, Chin-TengTeng, Chang, Che-Jui; Lin, Bor-Shyh; Hung, Shao-Hang;Chao, A Real-Time Wireless Brain–Computer Interface System for Drowsiness Detection, IEEE Transactions on Biomedical Circuits and Systems (2010) ,214-222.

      [17] Lin, Chin-Teng Chin-Teng , Ko, Li-Wei; Chung,et al , Adaptive EEG-Based Alertness Estimation System by Using ICA-Based Fuzzy Neural Networks, IEEE Transactions on Circuits and Systems I (2006), 2469 – 2476

      [18]B.G. Lee, S.J.Jung,WY.Chung, Real-time physiological and vision monitoring of vehicle driver for non-intrusive drowsiness detection, IET journal of Communications(2011),2461 – 2469

      [19] Lin, Chin-TengTeng, Chang, Che-Jui; Lin, Bor-Shyh; Hung, Shao-Hang;Chao, A Real-Time Wireless Brain–Computer Interface System for Drowsiness Detection, IEEE Transactions on Biomedical Circuits and Systems (2010), 214-222


 

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Article ID: 26741
 
DOI: 10.14419/ijet.v7i3.20.26741




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