Omnet++ Simulation of Facial Nerve Monitoring in Real Time Neurosurgery Based on WBAN

  • Asma AmmariEmail author
  • Rachida Saouli
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 914)


Neurosurgery is one of the most critical medical fields. The neurosurgeons deal with nerves sensitive situations such as paralysis. For the sake of avoiding those risks, the neurosurgeon operates while the patient is partly awake. We are interested in this paper to handle the case of the facial nerve which can be altered during an intervention at the ponto-cerebellar angle specialty of a neurosurgeon expert [1]. In this case wired systems, based on electromyography “EMG” technology, were used in parallel with visual monitoring. However, we have proposed a model of automated system based on Wireless Body Area Networks “WBAN” for facial nerves intraoperative monitoring. Our model is based on active synchronized stimulations. For the aim of assuming the patient comfort also, to add more flexibility to the neurosurgery our proposed model benefits from wireless communication instead of wired connections. We distinguish four scenarios deployed according to the facial muscles anatomy and simulated using OMNet++. The results, obtained by comparing the four scenarios, allowed us to define the optimal scenario according to a set of criteria (the system delivery time, the communication time, the energy consumed, and data processing time).


Neurosurgery Facial nerve monitoring WBAN OMNet++ 


  1. 1.
    Boublata, L.: La fonction du nerf facial et la qualité de l’exérèse des schwannomes vestibulaires géants et larges opérés par voie rétrosigmoide transméatale.. Key note lecture congrès WFNS Rome (2015)Google Scholar
  2. 2.
    “Neurosurgery” Spine-health. Accessed 09 Aug 2018
  3. 3.
    Guntinas-Lichius, O., Eisele, D.W.: Facial nerve monitoring. Adv. Otorhinolaryngol. 78, 46–52 (2016)Google Scholar
  4. 4.
    Val, T., Campo, E., Van Den Bosschz, A.: Technologie ZigBee/802.15.4 : Protocoles, topologies et domaines d’application. Techniques de l’Ingenieur TE7508, 8 (2008)Google Scholar
  5. 5.
    Kurunathan, J.H.: Study and overview on WBAN under IEEE 802.15.6. U. Porto J. Eng. 1(1), 11–21 (2015)CrossRefGoogle Scholar
  6. 6.
    El Chaoui, N.E., Bouayad, A., El Ghazi, M., Bekkali, M.: Modeling and simulation of a wireless body area network for monitoring sick patient remotely. Int. J. Comput. Sci. Inf. Technol. 6(1), 580–585 (2015)Google Scholar
  7. 7.
    Shobha, G., Chittal, R.R., Kumar, K.: Medical applications of wireless networks. In: Second International Conference on IEEE Systems and Networks Communications, ICSNC, p. 82, August 2007Google Scholar
  8. 8.
    Ngoc, T.V.: Medical Applications of Wireless Networks, April 2008Google Scholar
  9. 9.
    Otto, C., Milenkovic, A., Sanders, C., Jovanov, E.: System architecture of a wireless body area sensor network for ubiquitous health monitoring. J. Mobile Multimed. 1, 307–326 (2006)Google Scholar
  10. 10.
    Singh, G.D., Saini, D.S.: Arrogyam: arrhythmia detection for ambulatory patient monitoring. In: Contemporary Computing, pp. 168–180 (2010)Google Scholar
  11. 11.
    Aminian, M., Naji, H.R.: A hospital healthcare monitoring system using wireless sensor networks. J. Health Med. Inform. 4(2), 1–6 (2013)CrossRefGoogle Scholar
  12. 12.
    Latha, R., Vetrivelan, P., Jagannath, M.: Balancing emergency message dissemination and network lifetime in wireless body area network using ant colony optimization and Bayesian game formulation. Inf. Med. Unlocked 8, 60–65 (2017)CrossRefGoogle Scholar
  13. 13.
    Borujeny, G.T., Yazdi, M., Keshavarz-Haddad, A., Borujeny, A.R.: Detection of epileptic seizure using wireless sensor networks. J. Med. Signals Sens. 3(2), 63–68 (2013)Google Scholar
  14. 14.
    King, R.C., Atallah, L., Lo, B.P., Yang, G.-Z.: Development of a wireless sensor glove for surgical skills assessment. IEEE Trans. Inf. Technol. Biomed. 13(5), 673–679 (2009). Publ. IEEE Eng. Med. Biol. Soc.CrossRefGoogle Scholar
  15. 15.
    Kiourti, A., Wang, Z., Lee, C., Scwerdt, H., Chae, J., Volakis, J.L.: A wireless neurosensing system for remote monitoring of brain signals. In: The 8th European Conference on Antennas and Propagation (EuCAP 2014), pp. 3452–3453 (2014)Google Scholar
  16. 16.
    Choi, C.Q.: Wireless ‘Neural Dust’ Could Monitor Your Brain. Accessed 09 June 2018
  17. 17.
    Maharbiz, M.M., Seo, D.J., Alon, E., Carmena, J., Rabaey, J.: Tutorial_BioCAS2014_slides Neural Dust (2014)Google Scholar
  18. 18.
    Staff, I.: Nanotech tattoo maps emotions and monitors muscle activity. Accessed 09 June 2018
  19. 19.
    Boulacel, A.: Facial nerve and Wrisberg Intermediate Nerve - Le NERF FACIAL et nerf intermédiaire. Course Wrisberg Laboratory of Human Anatomy dz, Second year Medicine (2017)Google Scholar

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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Computer ScienceUniversity of BiskraBiskraAlgeria
  2. 2.National Engineering School of Sfax (ENIS)University of SfaxSfaxTunisia

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