Advertisement

Towards a New Generation of Wheelchairs Sensitive to Emotional Behavior of Disabled People

  • Mohamed Moncef Ben Khelifa
  • Hachem A. Lamti
  • Adel M. Alimi
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 735)

Abstract

The purpose of this article is to present a new alternative to handle wheelchair command and control especially for palsied patients. This project proposes a new framework based on visual and cerebral activities which are mapped into command/control and security blocks. While the former deals with the migration from a joystick-based navigation to a brain/gaze-based one, the latter enhances security by accounting for human factors. Those are assessed through emotions. Four emotions were induced and measured (relaxation, nervousness, excitement and stress) in three navigation scenarios where the introduction of the detection block was assessed. Based on those findings, an emotion block is built.

References

  1. 1.
    Jong, K.: Learning with genetic algorithms: an overview. Mach. Learn. 3(2–3), 121–138 (1988)Google Scholar
  2. 2.
    Lamti, H.A., Ben Khelifa, M.M., Alimi, A.M., Gorce, P.: Effect of fatigue on ssvep during virtual wheelchair navigation. J. Theor. Appl. Inf. Technol. 65, 1–10 (2014)Google Scholar
  3. 3.
    Lamti, H.A., Ben Khelifa, M.M., Alimi, A.M., Gorce, P.: Emotion detection for wheelchair navigation enhancement. Robotica 34(6), 1209–1226 (2016)CrossRefGoogle Scholar
  4. 4.
    Lamti, H.A., Gorce, P., Ben Khelifa, M.M., Alimi, A.M.: When mental fatigue can be distinguished by event related potential (p300) during virtual wheelchair navigation. Comput. Methods Biomech. Biomed. Eng. 19(16), 1749–1759 (2016)CrossRefGoogle Scholar
  5. 5.
    Molina, G., Tsoneva, T., Nijholt, A.: Emotional brain-computer interfaces. In: 3rd International Conference on Affective Computing and Intelligent Interaction and Workshops, ACII 2009, pp. 1–9, September 2009Google Scholar
  6. 6.
    Ren, M., Karimi, H.: A fuzzy logic map matching for wheelchair navigation. GPS Solut. 16(3), 273–282 (2012)CrossRefGoogle Scholar
  7. 7.
    Urdiales, C., Perez, E., Peinado, G., Fdez-Carmona, M., Peula, J., Annicchiarico, R., Sandoval, F., Caltagirone, C.: On the construction of a skill-based wheelchair navigation profile. IEEE Trans. Neural Syst. Rehabil. Eng. 21(6), 917–927 (2013)CrossRefGoogle Scholar
  8. 8.
    Vander Poorten, E.B., Demeester, E., Hüntemann, A., Reekmans, E., Philips, J., De Schutter, J.: Backwards maneuvering powered wheelchairs with haptic guidance. In: Proceedings of the 2012 International Conference on Haptics: Perception, Devices, Mobility, and Communication - Part I, EuroHaptics 2012, pp. 419–431. Springer, Berlin, Heidelberg (2012)Google Scholar
  9. 9.
    Yuen, C.: On the smoothed periodogram method for spectrum estimation. Sig. Process. 1(1), 83–86 (1979)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Mohamed Moncef Ben Khelifa
    • 1
  • Hachem A. Lamti
    • 1
  • Adel M. Alimi
    • 2
  1. 1.Bio-modélisation et Ingénierie des Handicaps (HANDIBIO) LaboratorySouth UniversityToulon-VarFrance
  2. 2.Research Group on Intelligent Machines (REGIM) LaboratoryNational Engineering School of SfaxSfaxTunisia

Personalised recommendations