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Development of Innovative HMI Strategies for Eye Controlled Wheelchairs in Virtual Reality

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Augmented Reality, Virtual Reality, and Computer Graphics (AVR 2016)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9769))

Abstract

This paper focuses on the development of a gaze-based control strategy for semiautonomous wheelchairs. Starting from the information gathered by an eye tracker, the work aims to develop a novel paradigm of Human Computer Interaction (HCI) by means of a Virtual Reality (VR) environment, where specific motion metrics are evaluated.

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References

  1. Ktena, S.I., Abbott, W., Aldo Faisal, A.: A virtual reality platform for safe evaluation and training of natural gaze-based wheelchair driving. In: 2015 7th International IEEE/EMBS Conference on Neural Engineering (NER). IEEE (2015)

    Google Scholar 

  2. Buxbaum, L.J., Palermo, M.A., Mastrogiovanni, D., Read, M.S., Rosenberg-Pitonyak, E., Rizzo, A.A., Coslett, H.B.: Assessment of spatial attention and neglect with a virtual wheelchair navigation task. J. Clin. Exp. Neuropsychol. 30(6), 650–660 (2008)

    Article  Google Scholar 

  3. Cooper, R.A., et al.: Virtual reality and computer-enhanced training applied to wheeled mobility: an overview of work in Pittsburgh. Assist. Technol. 17(2), 159–170 (2005)

    Article  Google Scholar 

  4. Fornaser, A., De Cecco, M., Leuci, M., Conci, N., Daldoss, M., Maule, L., De Natale, F., Da Lio, M.: Eye trackers uncertainty analysis and modelling. XXIII Convegno Nazionale A.I.VE.LA., Perugia, 12–13 November 2015

    Google Scholar 

  5. Armanini, A.; Conci, N.: Eye tracking as an accessible assistive tool. In: 2010 11th International Workshop on Image Analysis for Multimedia Interactive Services (WIAMIS), pp. 1–4, 12–14 April 2010

    Google Scholar 

  6. Mahajan, H.P., et al.: Assessment of wheelchair driving performance in a virtual reality-based simulator. J. Spinal Cord Med. 36(4), 322–332 (2013)

    Article  MathSciNet  Google Scholar 

  7. Champaty, B., et al.: Development of EOG based human machine interface control system for motorized wheelchair. In: 2014 Annual International Conference on Emerging Research Areas: Magnetics, Machines and Drives (AICERA/iCMMD). IEEE (2014)

    Google Scholar 

  8. Jain, M., Puri, S., Unishree, S.: Eyeball motion controlled wheelchair using IR sensors. World Acad. Sci. Eng. Technol. Int. J. Comput. Electr. Autom. Control Inf. Eng. 9(4), 906–909 (2015)

    Google Scholar 

  9. Clemotte, A., Velasco, M., Torricelli, D., Raya, R., Ceres, R.: Accuracy and precision of the Tobii X2-30 eye-tracking under non ideal conditions. In: Proceedings of the 2nd International Congress on Neurotechnology, Electronics and Informatics, pp. 111–116 (2014)

    Google Scholar 

  10. Wood, J.M., Troutbeck, R.: Effect of visual impairment on driving. Hum. Factors: J. Hum. Factors Ergon. Soc. 36(3), 476–487 (1994)

    Google Scholar 

  11. Wood, J.M., Troutbeck, R.: Effect of restriction of the binocular visual field on driving performance. Ophthalmic Physiol. Opt. 12(3), 291–298 (1992)

    Article  Google Scholar 

  12. Wood, J.M., Mallon, K.: Comparison of driving performance of young and old drivers (with and without visual impairment) measured during in-traffic conditions. Optom. Vis. Sci. 78(5), 343–349 (2001)

    Article  Google Scholar 

  13. Lövsund, P., Hedin, A.: Effects on driving performance of visual field defects (1986)

    Google Scholar 

  14. Sodhi, M., et al.: Driver Performance Evaluation: Considerations Underlying Selection and Design of Routes. Vision in Vehicles X. Elsevier Sciences Publishers, Amsterdam (2005)

    Google Scholar 

  15. Peli, E.: Driving with low vision: who, where, when, and why. Albert Jokobiec’s Princ. Pract. Ophthalmol. 4, 5369–5376 (2008). Elsevier

    Article  Google Scholar 

  16. Bowers, A., et al.: On-road driving with moderate visual field loss. Optom. Vis. Sci. 82(8), 657–667 (2005)

    Article  Google Scholar 

  17. Odenheimer, G.L., et al.: Performance-based driving evaluation of the elderly driver: safety, reliability, and validity. J. Gerontol. 49(4), M153–M159 (1994)

    Article  Google Scholar 

  18. Carr, D., et al.: The effect of age on driving skills. J. Am. Geriatr. Soc. 40(6), 567–573 (1992)

    Article  MathSciNet  Google Scholar 

  19. Kamaraj, D.C., et al.: Quantifying power wheelchair driving ability. In: Conference Proceedings, RESNA (2014)

    Google Scholar 

  20. Castellanos, J.C., Susin, A.A., Fruett, F.: Embedded sensor system and techniques to evaluate the comfort in public transportation. In: 2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC). IEEE (2011)

    Google Scholar 

  21. ISO 2631/1: Evaluation of human exposure to whole body vibration - Part 1: general requirements. International Organization for Standardization, Geneva, Switzerland (1985)

    Google Scholar 

  22. Hoberock, L.L.: A survey of longitudinal acceleration comfort studies in ground transportation vehicles. J. Dyn. Syst. Meas. Control 99(2), 76–84 (1977)

    Article  Google Scholar 

  23. Lin, C.-S., et al.: Powered wheelchair controlled by eye-tracking system. Opt. Appl. 36(2/3), 401 (2006)

    Google Scholar 

  24. Gajwani, P.S., Chhabria, S.A.: Eye motion tracking for wheelchair control. Int. J. Inf. Technol. 2(2), 185–187 (2010)

    Google Scholar 

  25. Wästlund, E., et al.: Evaluating gaze-driven power wheelchair with navigation support for persons with disabilities. J. Rehabil. Res. Dev. 52(7), 815 (2015)

    Article  Google Scholar 

  26. Pingali, T.R., Dubey, S., Shivaprasad, A., Varshney, A., Ravishankar, S., Pingali, G.R., Polisetty, N.K., Manjunath, N., Padmaja, K.Y.: Eye-gesture controlled intelligent wheelchair using electro-oculography. In: 2014 IEEE International Symposium on Circuits and Systems (ISCAS), pp. 2065–2068, 1–5 June 2014

    Google Scholar 

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Correspondence to Mariolino De Cecco .

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Maule, L., Fornaser, A., Leuci, M., Conci, N., Da Lio, M., De Cecco, M. (2016). Development of Innovative HMI Strategies for Eye Controlled Wheelchairs in Virtual Reality. In: De Paolis, L., Mongelli, A. (eds) Augmented Reality, Virtual Reality, and Computer Graphics. AVR 2016. Lecture Notes in Computer Science(), vol 9769. Springer, Cham. https://doi.org/10.1007/978-3-319-40651-0_29

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  • DOI: https://doi.org/10.1007/978-3-319-40651-0_29

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-40650-3

  • Online ISBN: 978-3-319-40651-0

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