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Enhancing Drone Pilots’ Engagement Through a Brain-Computer Interface

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Human-Computer Interaction. Multimodal and Natural Interaction (HCII 2020)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12182))

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Abstract

Drones are becoming ubiquitous in society, and as their use continues to grow, it becomes important to research new approaches to provide a better user experience and safer flights. In this paper, we propose the use of brain-computer interfaces (BCI) to measure the drone pilot’s engagement from the brain while piloting drones. We hypothesize that relaying on a quantified measurement, the pilot will be encouraged to increase their focus, leading to higher engagement and possible safer flights. Our first contribution is a technical description of the system, which allows the pilots to control a virtual first-person view (FPV) drone while receiving feedback on their engagement level measured with a BCI. Secondly, we present the results of a user study with 10 participants, in which their feedback stated that receiving engagement level feedback increased their engagement as they tried to raise their focus in the activity.

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Notes

  1. 1.

    Figure 1 acquired from g.Tec Nautilus user manual.

References

  1. Abdelrahman, Y., Hassib, M., Marquez, M.G., Funk, M., Schmidt, A.: Implicit engagement detection for interactive museums using brain-computer interfaces. In: Proceedings of the 17th International Conference on Human-Computer Interaction with Mobile Devices and Services Adjunct, pp. 838–845 (2015)

    Google Scholar 

  2. Abtahi, P., Zhao, D.Y., E, J.L., Landay, J.A.: Drone near me: exploring touch-based human-drone interaction. Proc. ACM Interact. Mob. Wearable Ubiquit. Technol. 1(3), 1–8 (2017)

    Article  Google Scholar 

  3. Federal Aviation Administration: Unmanned aircraft systems forecast (2019). https://www.faa.gov/data_research/aviation/aerospace_forecast. Accessed 27 Jan 2020

  4. Andujar, M., Gilbert, J.E.: Let’s learn! Enhancing user’s engagement levels through passive brain-computer interfaces. In: CHI 2013 Extended Abstracts on Human Factors in Computing Systems, pp. 703–708. ACM (2013)

    Google Scholar 

  5. Apvrille, L., Tanzi, T., Dugelay, J.L.: Autonomous drones for assisting rescue services within the context of natural disasters. In: 2014 XXXIth URSI General Assembly and Scientific Symposium (URSI GASS), pp. 1–4. IEEE (2014)

    Google Scholar 

  6. Barin, A., Dolgov, I., Toups, Z.O.: Understanding dangerous play: a grounded theory analysis of high-performance drone racing crashes. In: Proceedings of the Annual Symposium on Computer-Human Interaction in Play, pp. 485–496. ACM (2017)

    Google Scholar 

  7. Boyle, M.J.: The race for drones. Orbis 59(1), 76–94 (2015)

    Article  Google Scholar 

  8. Cauchard, J.R., Zhai, K.Y., Spadafora, M., Landay, J.A.: Emotion encoding in human-drone interaction. In: 2016 11th ACM/IEEE International Conference on Human-Robot Interaction (HRI), pp. 263–270. IEEE (2016)

    Google Scholar 

  9. Hassib, M., Schneegass, S., Eiglsperger, P., Henze, N., Schmidt, A., Alt, F.: EngageMeter: a system for implicit audience engagement sensing using electroencephalography. In: Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, pp. 5114–5119 (2017)

    Google Scholar 

  10. Hing, J.T., Sevcik, K.W., Oh, P.Y.: Improving unmanned aerial vehicle pilot training and operation for flying in cluttered environments. In: 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 5641–5646. IEEE (2009)

    Google Scholar 

  11. Klem, G.H., Lüders, H.O., Jasper, H., Elger, C., et al.: The ten-twenty electrode system of the international federation. Electroencephalogr. Clin. Neurophysiol. 52(3), 3–6 (1999)

    Google Scholar 

  12. Kosmyna, N., Sarawgi, U., Maes, P.: AttentivU: evaluating the feasibility of biofeedback glasses to monitor and improve attention. In: Proceedings of the 2018 ACM International Joint Conference and 2018 International Symposium on Pervasive and Ubiquitous Computing and Wearable Computers, pp. 999–1005 (2018)

    Google Scholar 

  13. Nadobnik, J., et al.: The use of drones in organizing the Olympic games. Handel Wewnętrzny 365(6), 288–299 (2016)

    Google Scholar 

  14. Nourmohammadi, A., Jafari, M., Zander, T.O.: A survey on unmanned aerial vehicle remote control using brain-computer interface. IEEE Trans. Hum.-Mach. Syst. 48(4), 337–348 (2018)

    Article  Google Scholar 

  15. Puri, V., Nayyar, A., Raja, L.: Agriculture drones: a modern breakthrough in precision agriculture. J. Stat. Manag. Syst. 20(4), 507–518 (2017)

    Google Scholar 

  16. Rao, B., Gopi, A.G., Maione, R.: The societal impact of commercial drones. Technol. Soc. 45, 83–90 (2016)

    Article  Google Scholar 

  17. Sumwalt, R.L., Thomas, R., Dismukes, K.: Enhancing flight-crew monitoring skills can increase flight safety. In: Annual International Air Safety Seminar, vol. 55, pp. 175–206. Flight Safety Foundation 1998 (2002)

    Google Scholar 

  18. Temma, R., Takashima, K., Fujita, K., Sueda, K., Kitamura, Y.: Third-person piloting: increasing situational awareness using a spatially coupled second drone. In: Proceedings of the 32nd Annual ACM Symposium on User Interface Software and Technology, pp. 507–519 (2019)

    Google Scholar 

  19. Tezza, D., Andujar, M.: The state-of-the-art of human-drone interaction: a survey. IEEE Access 7, 167438–167454 (2019)

    Article  Google Scholar 

  20. Tezza, D., Garcia, S., Hossain, T., Andujar, M.: Brain eRacing: an exploratory study on virtual brain-controlled drones. In: Chen, J.Y.C., Fragomeni, G. (eds.) HCII 2019. LNCS, vol. 11575, pp. 150–162. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-21565-1_10

    Chapter  Google Scholar 

  21. Watson, D., Clark, L.A., Tellegen, A.: Development and validation of brief measures of positive and negative affect: the PANAS scales. J. Pers. Soc. Psychol. 54(6), 1063 (1988)

    Article  Google Scholar 

  22. Yu, Y., et al.: FlyingBuddy2: a brain-controlled assistant for the handicapped. In: Ubicomp, pp. 669–670. Citeseer (2012)

    Google Scholar 

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Author information

Authors and Affiliations

  1. University of South Florida, Tampa, FL, 33620, USA

    Tracy Pham, Dante Tezza & Marvin Andujar

Authors
  1. Tracy Pham
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  2. Dante Tezza
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  3. Marvin Andujar
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Corresponding author

Correspondence to Dante Tezza .

Editor information

Editors and Affiliations

  1. The Open University of Japan, Chiba, Japan

    Masaaki Kurosu

Appendix

Appendix

OpenVibe script for processing EEG data and calculating engagement.

figure a

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Pham, T., Tezza, D., Andujar, M. (2020). Enhancing Drone Pilots’ Engagement Through a Brain-Computer Interface. In: Kurosu, M. (eds) Human-Computer Interaction. Multimodal and Natural Interaction. HCII 2020. Lecture Notes in Computer Science(), vol 12182. Springer, Cham. https://doi.org/10.1007/978-3-030-49062-1_49

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  • DOI: https://doi.org/10.1007/978-3-030-49062-1_49

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-49061-4

  • Online ISBN: 978-3-030-49062-1

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