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Developing a 3D Laparoscopy Training Application to Assess the Efficacy in Virtual Reality Environments

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Smart Objects and Technologies for Social Good (GOODTECHS 2023)

Abstract

This study aims to develop a multimodal understanding of transferring an established method of laparoscopy training to the virtual reality domain. The virtual reality version of the laparoscopic box trainer is developed and tested with 15 participants. Post-experiment questionnaires showed the version of the simulation with tutorial and haptic feedback is acceptable in terms of usability and received better feedback in the technology acceptance model questionnaire. Furthermore, the kinematic behavior of participants’ hands showed a significant distinction between above-average and below-average completion time groups similar to the physical and computer-based non-immersive simulation counterparts. The physiological response of the participants is investigated between rest state and during the task with an Electrocardiogram (ECG) and indicators of increased mental workload are observed with increased heart rate and decreased heart rate variability. The interest in assessing the physiological and kinematic features of trainees in a virtual reality (VR) environment is on the rise and the proposed study is very promising in terms of enhancing the development of improved training and assessment methodologies.

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Notes

  1. 1.

    Surgical Science Ltd., Gothenburg, Sweden, https://surgicalscience.com/simulators/lapsim/, Last accessed: 2023–07-01.

  2. 2.

    Unity Real-Time Development Platform, https://unity.com, Last accessed: 2023–06-28.

References

  1. Choy, I., Kitto, S., Adu-Aryee, N., Okrainec, A.: Barriers to the uptake of laparoscopic surgery in a lower-middle-income country. Surg. Endosc. 27(11), 4009–4015 (2013). https://doi.org/10.1007/S00464-013-3019-Z

    Article  Google Scholar 

  2. Lim, S., Ghosh, S., Niklewski, P., Roy, S.: Laparoscopic suturing as a barrier to broader adoption of laparoscopic surgery. JSLS : J. Soci. Laparoendosc. Surg. 21(3) (2017). https://doi.org/10.4293/JSLS.2017.00021

  3. Dhariwal, A., Prabhu, R., Dalvi, A., Supe, A.: Effectiveness of box trainers in laparoscopic training. J. Minim. Access Surg. 3(2), 57 (2007). https://doi.org/10.4103/0972-9941.33274

    Article  Google Scholar 

  4. Logishetty, K., Rudran, B., Cobb, J.P.: Virtual reality training improves trainee performance in total hip arthroplasty: a randomized controlled trial. Bone Joint J. 101-B(12), 1585–1592 (2019). https://doi.org/10.1302/0301-620X.101B12.BJJ-2019-0643.R1

  5. Gurusamy, K.S., Aggarwal, R., Palanivelu, L., Davidson, B.R.: Virtual reality training for surgical trainees in laparoscopic surgery. Cochrane Database Syst. Rev. 1 (2009).https://doi.org/10.1002/14651858.CD006575.PUB2

  6. Gallagher, A.G., et al.: Virtual reality simulation for the operating room: proficiency-based training as a paradigm shift in surgical skills training. Ann. Surg. 241(2), 364 (2005). https://doi.org/10.1097/01.SLA.0000151982.85062.80

    Article  Google Scholar 

  7. Seymour, N.E., et al.: Virtual reality training improves operating room performance: results of a randomized. Double-Blinded Study. Ann. Surg. 236(4), 458 (2002). https://doi.org/10.1097/00000658-200210000-00008

    Article  Google Scholar 

  8. Wilson, M.S., Middlebrook, A., Sutton, C., Stone, R., McCloy, R.F.: MIST VR: a virtual reality trainer for laparoscopic surgery assesses performance. Ann. R. Coll. Surg. Engl. 79(6), 403 (1997)

    Google Scholar 

  9. Diesen, D.L., et al.: Effectiveness of laparoscopic computer simulator versus usage of box trainer for endoscopic surgery training of novices. J. Surg. Educ. 68(4), 282–289 (2011). https://doi.org/10.1016/J.JSURG.2011.02.007

    Article  Google Scholar 

  10. Zakeri, Z., Mansfield, N., Sunderland, C., Omurtag, A.: Physiological correlates of cognitive load in laparoscopic surgery. Sci. Rep. 10(1), 1–13 (2020). https://doi.org/10.1038/s41598-020-69553-3

  11. Keles, H.O., Cengiz, C., Demiral, I., Ozmen, M.M., Omurtag, A.: High density optical neuroimaging predicts surgeons’s subjective experience and skill levels. PLoS ONE 16(2), e0247117 (2021). https://doi.org/10.1371/JOURNAL.PONE.0247117

    Article  Google Scholar 

  12. Hirachan, N., Mathews, A., Romero, J., Rojas, R.F.: Measuring cognitive workload using multimodal sensors. In: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS,pp. 4921–4924. (2022). https://doi.org/10.1109/EMBC48229.2022.9871308

  13. Zhou, T., Cha, J.S., Gonzalez, G., Wachs, J.P., Sundaram, C.P., Yu, D.: Multimodal physiological signals for workload prediction in robot-assisted surgery. ACM Trans. Hum.-Robot Interact. (THRI) 9(2), 1–26 (2020). https://doi.org/10.1145/3368589

    Article  Google Scholar 

  14. Dey, A., Chatourn, A., Billinghurst, M.: Exploration of an EEG-based cognitively adaptive training system in virtual reality. In: 26th IEEE Conference on Virtual Reality and 3D User Interfaces, pp. 220–226 (2019). https://doi.org/10.1109/VR.2019.8797840

  15. Yu, P., et al.: Cognitive load/flow and performance in virtual reality simulation training of laparoscopic surgery. In: Proceedings - 2021 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW, pp. 466–467 (2021). https://doi.org/10.1109/VRW52623.2021.00115

  16. Antoniou, P.E., et al.: Biosensor real-time affective analytics in virtual and mixed reality medical education serious games: cohort study. JMIR Serious Games 8(3), e17823 (2020). https://doi.org/10.2196/17823

  17. Brooke, J.: SUS-A quick and dirty usability scale. In: Patrick, W., Jordan, B., Thomas, Ian Lyall McClelland., Weerdmeester, B (eds.), Usability Evaluation In Industry, pp. 189–196. CRC Press (1996)

    Google Scholar 

  18. Venkatesh, V., Davis, F.D.: A model of the antecedents of perceived ease of use: development and test. Decis. Sci. 27(3), 451–481 (1996). https://doi.org/10.1111/J.1540-5915.1996.TB00860.X

    Article  Google Scholar 

  19. Yosunkaya, E.: Developing a virtual reality adaptation of the laparoscopic surgical training: A multimodal study (Master’s Thesis). Middle East Technical University, Ankara, Türkiye (2023)

    Google Scholar 

  20. Ebina, K., et al.: Motion analysis for better understanding of psychomotor skills in laparoscopy: objective assessment-based simulation training using animal organs. Surg. Endosc. 35(8), 4399–4416 (2021). https://doi.org/10.1007/S00464-020-07940-7

    Article  Google Scholar 

  21. Makowski, D., et al.: NeuroKit2: a python toolbox for neurophysiological signal processing. Behav. Res. Methods 53(4), 1689–1696 (2021). https://doi.org/10.3758/S13428-020-01516-Y

    Article  Google Scholar 

  22. Brookhuis, K.A., de Waard, D.: Monitoring drivers’ mental workload in driving simulators using physiological measures. Accid. Anal. Prev. 42(3), 898–903 (2010). https://doi.org/10.1016/J.AAP.2009.06.001

    Article  Google Scholar 

  23. Taelman, J., Vandeput, S., Gligorijević, I., Spaepen, A., Van Huffel, S.: Time-frequency heart rate variability characteristics of young adults during physical, mental and combined stress in laboratory environment. In: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, pp. 1973–1976 (2011). https://doi.org/10.1109/IEMBS.2011.6090556

  24. Yurko, Y.Y., Scerbo, M.W., Prabhu, A.S., Acker, C.E., Stefanidis, D.: Higher mental workload is associated with poorer laparoscopic performance as measured by the NASA-TLX tool. Simul. Healthc. 5(5), 267–271 (2010). https://doi.org/10.1097/SIH.0B013E3181E3F329

    Article  Google Scholar 

  25. Zheng, B., Cassera, M.A., Martinec, D.V., Spaun, G.O., Swanström, L.L.: Measuring mental workload during the performance of advanced laparoscopic tasks. Surg. Endosc.Endosc. 24(1), 45–50 (2010). https://doi.org/10.1007/S00464-009-0522-3

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Modeling and Simulation, Graduate School of Informatics, Middle East Technical University, 06800, Ankara, Turkey

    Ege Yosunkaya & Elif Surer

  2. Department of Biomedical Engineering, Ankara University, 06830, Ankara, Turkey

    Sebahat Selin Şahin & Hasan Onur Keleş

Authors
  1. Ege Yosunkaya
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  2. Sebahat Selin Şahin
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  3. Elif Surer
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  4. Hasan Onur Keleş
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Correspondence to Ege Yosunkaya .

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Editors and Affiliations

  1. Polytechnic University of Leiria, Leiria, Portugal

    Paulo Jorge Coelho

  2. Instituto de Telecomunicações, Escola Superior de Tecnologia e Gestão de Águeda, Universidade de Aveiro, Águeda, Portugal

    Ivan Miguel Pires

  3. Polytechnic University of Leiria, Leiria, Portugal

    Nuno Vieira Lopes

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Yosunkaya, E., Şahin, S.S., Surer, E., Keleş, H.O. (2024). Developing a 3D Laparoscopy Training Application to Assess the Efficacy in Virtual Reality Environments. In: Coelho, P.J., Pires, I.M., Lopes, N.V. (eds) Smart Objects and Technologies for Social Good. GOODTECHS 2023. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 556. Springer, Cham. https://doi.org/10.1007/978-3-031-52524-7_6

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  • DOI: https://doi.org/10.1007/978-3-031-52524-7_6

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