DOI QR코드

DOI QR Code

Development of Online Speller using Non-contact Blink Detection Glasses

비접촉 눈 깜박임 측정 안경형 디바이스를 이용한 실시간 스펠러의 구현

  • Lee, Jeong Su (Interdisciplinary Program for Bioengineering, Graduate School, Seoul National University) ;
  • Lee, Hong Ji (Interdisciplinary Program for Bioengineering, Graduate School, Seoul National University) ;
  • Lee, Won Kyu (Interdisciplinary Program for Bioengineering, Graduate School, Seoul National University) ;
  • Lim, Yong Gyu (Department of Oriental Biomedical Engineering, Sangji University) ;
  • Park, Kwang Suk (Interdisciplinary Program for Bioengineering, Graduate School, Seoul National University)
  • 이정수 (서울대학교 대학원 협동과정 바이오엔지니어링 전공) ;
  • 이홍지 (서울대학교 대학원 협동과정 바이오엔지니어링 전공) ;
  • 이원규 (서울대학교 대학원 협동과정 바이오엔지니어링 전공) ;
  • 임용규 (상지대학교 한방의료공학과) ;
  • 박광석 (서울대학교 대학원 협동과정 바이오엔지니어링 전공)
  • Received : 2015.10.19
  • Accepted : 2015.12.19
  • Published : 2015.12.31

Abstract

We proposed blink based online speller for the locked-in syndrome (LIS) patients, paralyzed in nearly all voluntary muscles expect for the eyes, with a simple and easy-to-use eye blink detection glasses. Electrooculogram (EOG) is the golden standard method of eye movement or blink measurement with Ag/AgCl electrodes. However, this method has several drawbacks such as skin irritation and dehydration of conductive gel. To resolve the shortcomings, we used a blink detection system based on a transparent capacitively coupled electrode, which is conductive indium tin oxide (ITO) films. The films make it possible to measure eye blink without direct skin contact and obstruction of field of view. We finally developed user-friendly blink based online speller with the blink detection system. To classify voluntary and non-voluntary blink, we used the double blink for command of the speller. The online speller experiment result with six healthy subjects shows that mean accuracy is 98.96% and letter per minute (LPM) is 4.73, which are better result by comparison with conventional P300 or auditory brain-computer interface (BCI) paradigm. The result of the experiment demonstrates the possibility of applying the proposed system as a communication method for the LIS patients.

Keywords

References

  1. J.R. Wolpaw, N. Birbaumer, D.J. McFarland, G. Pfurtscheller, and T.M. Vaughan, "Brain-computer interfaces for communication and control," Clinical Neurophysiology, vol. 113, no. 6, pp. 797-791, 2002.
  2. T. Ebrahimi, J. Vesin, G Garcia, "Brain-computer interface in multimedia communication," IEEE Signal Processing Magazine, vol. 20, pp. 14-24, 2003.
  3. J.J. Daly, J.R. Wolpaw, "Brain-computer interfaces in neurological rehabilitation," Lancet Neurol, vol. 7, no. 11, pp. 1032-1043, 2008. https://doi.org/10.1016/S1474-4422(08)70223-0
  4. C.H. Lim, "Introduction to EEG-based Brain-Computer Interface (BCI) technology," J. Biomed Eng. Res., vol. 31, no. 1, pp. 1-13, 2010.
  5. J.S. Lee, Y.G. Lim, S.J. Kwon, and K.S. Park, "Non-contact blink detection glasses utilising transparent conductive film for binary communication," Electronics Letters, vol. 51, no. 5, pp. 382-384, 2015. https://doi.org/10.1049/el.2014.3548
  6. J. Hori, K. Sakano, and Y. Saitoh, "Development of communication supporting device controlled by eye movements and voluntary eye blink," Proc. 26th Annual International Conference of the IEEE EMBS, San Francisco, CA, USA, Sep. 2004, pp. 4302-4305.
  7. A.B. Usaki, S. Gurkan, F. Aloise, G. Vecchiato and F. Babiloni, "On the Use of Electrooculogram for Efficient Human Computer Interfaces," Computational intelligence and neuroscience, vol. 2010, 2010.
  8. M. Merino, O. River, I. Gomez, A. Molina and E. Dorronzoro, "A method of EOG signal processing to detect the direction of eye movements," Sensor Device Technologies and Applications (SENSORDEVICES), 2010 First International Conference on, pp. 100-105, 2010.
  9. Z. Lv, X.P. Wu, M. Li and D.X. Zhang, "Development of a human computer Interface system using EOG," Health, vol. 1, no.1, pp. 39-46, 2009. https://doi.org/10.4236/health.2009.11008
  10. K. Grauman, M. Betke, J. Lombardi, J. Gips, and G.R. Bradski, "Communication via eye blinks and eyebrow raises: video-based human-computer interfaces," Uni Access inf Soc, vol. 2, no. 4, pp. 359-373, 2003. https://doi.org/10.1007/s10209-003-0062-x
  11. S.R. Rupanagudi, N.S Vikas, V.C. Bharadwaj, N. Dhruva and K.S Sowmya, "Novel methodology for blink recognition using video oculography for communicating," Advances in Electrical Engineering (ICAEE), 2014 International Conference on, pp. 1-6, 2014.
  12. M. Chau and M.Betke, "Real time eye tracking and blink detection with usb cameras," Boston University Computer Science, vol. 2215, no. 2005-2012, pp. 1-10, 2005.
  13. A. Picot, S. Charbonnier and A. Caplier, "Drowsiness detection based on visual signs: blinking analysis based on high frame rate video," Instrumentation and Measurement Technology Conference (I2MTC), 2010 IEEE, pp. 801-804. 2010.
  14. Y.G. Lim, K.K. Kim, and K.S. Park, "ECG measurement on a chair without conductive contact," Biomedical Engineering, IEEE Transactions on, vol. 53, pp. 956-959, 2006. https://doi.org/10.1109/TBME.2006.872823
  15. J.S. Lee, J. Heo, W.K. Lee, Y.G. Lim, Y.H. Kim, and K.S. Park, "Flexible Capacitive Electrodes for Minimizing Motion Artifacts in Ambulatory Electrocardiogram," Sensors, vol. 14, no. 8, pp. 14732-14743, 2014. https://doi.org/10.3390/s140814732
  16. T. Matsuda and M. Makikawa, "ECG monitoring of a car driver using capacitively-coupled electrodes," Engineering in Medicine and Biology Society, 30th Annual International Conference of the IEEE, pp. 1315-1318, 2008.
  17. Y.G. Lim, K.K. Kim, and K.S. Park, "ECG recording on a bed during sleep without direct skin-contact," Biomedical Engineering, IEEE Transactions on, vol. 54, pp. 718-725, 2007. https://doi.org/10.1109/TBME.2006.889194
  18. L.A. Farwell and E Donchin, "Talking off the top of your head: toward a mental prosthesis utilizing event-related brain potentials," Electroencephalography and clinical Neurophysiology, vol. 70, no. 6, pp. 510-523, 1988. https://doi.org/10.1016/0013-4694(88)90149-6
  19. E. Ponder, and W.P. Kennedy, "On the act of blinking," Exp physiol, vol. 18, pp. 89-119, 1928.
  20. A.R. Bentivoglio, S.B. Bressman, E. Cassetta, D. Carretta, P. Tonali, and A. Albanese, "Analysis of blink rate patterns in normals," Movement Disorders, vol. 12, no. 6, pp. 1028-1034, 1997. https://doi.org/10.1002/mds.870120629
  21. I. Volosyak, "SSVEP-based Bremen-BCI interface-boosting information transfer rates," Journal of neural engineering, vol. 8, no. 3.
  22. I. Volosyak, D Valbuena, T Malechka, J Peuscher and A Graser, "Brain-computer interface using water-based electrodes," J. Neural Eng., vol. 7, no. 6, pp. 066007, 2010. https://doi.org/10.1088/1741-2560/7/6/066007
  23. H.J. Baek, H.S. Kim, H. Jeong, Y.G. Lim and K.S. Park, "Brain-computer interfaces using capacitive measurement of visual or auditory steady-state responses," J. Neural Eng., vol. 10, no. 2, pp. 024001, 2013. https://doi.org/10.1088/1741-2560/10/2/024001
  24. E. Donchin, K.M. Spencer and R. Wijesinghe, "The mental prosthesis: assessing the speed of a P300-based brain-computer interface," Rehabilitation Engineering, IEEE Transactions on, vol. 8, no. 2, pp. 174-179, 2000. https://doi.org/10.1109/86.847808
  25. D.W. Kim, J.C. Lee, Y.M. Park, I.Y. Kim and C.H. Lim, "Auditory brain-computer interfaces (BCIs) and their practical applications," Biomedical Engineering Letters, vol. 2, no. 1, pp. 13-17, 2012. https://doi.org/10.1007/s13534-012-0051-1
  26. J. Hohne, M. Schreuder, B. Blankertz and M. Tangermann, "A novel 9-class auditory ERP paradigm driving a predictive text entry system," Frontiers in neuroscience, vol. 5, 2011.