Volume 14, Issue 5 (Journal of Control, Vol. 14, No. 5, Special Issue on COVID-19 2021)                   JoC 2021, 14(5): 121-125 | Back to browse issues page

XML Persian Abstract Print

Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Heidari R, Motaharifar M, Taghirad H, Mohammadi S, Lashay A. A Review on Applications of Haptic Systems, Virtual Reality, and Artificial Intelligence in Medical Training in COVID-19 Pandemic. JoC. 2021; 14 (5) :121-125
URL: http://joc.kntu.ac.ir/article-1-819-en.html
1- K. N. Toosi University of Technology
2- Esfahan University
3- Tehran University Medical Sciences
Abstract:   (222 Views)
This paper presents a survey on haptic technology, virtual reality, and artificial intelligence applications in medical training during the COVID-19 pandemic. Over the last few decades, there has been a great deal of interest in using new technologies to establish capable approaches for medical training purposes. These methods are intended to minimize surgery's adverse effects, mostly when done by an inexperienced surgeon. Due to the world's unique situation during the pandemic, which causes several cities to be locked up, these methodologies are becoming more critical. They eliminate the physical contact requirement between medical personnel and fellows, which decreases the risk of being infected with the virus. This study aims to present new applications for haptic technology, virtual reality, artificial intelligence, and new fields where they can provide a viable solution in the COVID-19 pandemic or any other similar crises.
Full-Text [PDF 287 kb]   (111 Downloads)    
Type of Article: Review paper | Subject: COVID-19
Received: 2020/12/30 | Accepted: 2021/02/15 | Published: 2021/02/28

1. A. Biswas, U. Bhattacharjee, A. K. Chakrabarti, D. N. Tewari, H. Banu, and S. Dutta, "Emergence of Novel Coronavirus and COVID-19: whether to stay or die out?," Critical reviews in microbiology, vol. 46, no. 2, pp. 182-193, 2020. [DOI:10.1080/1040841X.2020.1739001]
2. "COVID-19 CORONAVIRUS PANDEMIC." worldmeter. https://www.worldometers.info/coronavirus/ (accessed December 26, 2020).
3. N. Subbaraman, "Who gets a COVID vaccine first? Access plans are taking shape," Nature, vol. 17, 2020. [DOI:10.1038/d41586-020-02684-9]
4. C. Hodges, S. Moore, B. Lockee, T. Trust, and A. Bond, "The difference between emergency remote teaching and online learning," Educause Review, vol. 27, 2020.
5. W. Zhang, Y. Wang, L. Yang, and C. Wang, "Suspending classes without stopping learning: China's education emergency management policy in the COVID-19 Outbreak," ed: Multidisciplinary Digital Publishing Institute, 2020. [DOI:10.3390/jrfm13030055]
6. M. de Notaris et al., "A three-dimensional computer-based perspective of the skull base," World neurosurgery, vol. 82, no. 6, pp. S41-S48, 2014. [DOI:10.1016/j.wneu.2014.07.024]
7. K. Kurzhals, M. Burch, T. Pfeiffer, and D. Weiskopf, "Eye tracking in computer-based visualization," Computing in Science & Engineering, vol. 17, no. 5, pp. 64-71, 2015. [DOI:10.1109/MCSE.2015.93]
8. M. Kersten-Oertel et al., "Augmented reality in neurovascular surgery: feasibility and first uses in the operating room," International journal of computer assisted radiology and surgery, vol. 10, no. 11, pp. 1823-1836, 2015. [DOI:10.1007/s11548-015-1163-8]
9. M. A. Lerner, M. Ayalew, W. J. Peine, and C. P. Sundaram, "Does training on a virtual reality robotic simulator improve performance on the da Vinci® surgical system?," Journal of Endourology, vol. 24, no. 3, pp. 467-472, 2010. [DOI:10.1089/end.2009.0190]
10. Y.-X. Hung, P.-C. Huang, K.-T. Chen, and W.-C. Chu, "What do stroke patients look for in game-based rehabilitation: a survey study," Medicine, vol. 95, no. 11, 2016. [DOI:10.1097/MD.0000000000003032]
11. S. S. Nudehi, R. Mukherjee, and M. Ghodoussi, "A shared-control approach to haptic interface design for minimally invasive telesurgical training," IEEE Transactions on Control Systems Technology, vol. 13, no. 4, pp. 588-592, 2005. [DOI:10.1109/TCST.2004.843131]
12. M. Motaharifar, H. D. Taghirad, K. Hashtrudi-Zaad, and S. F. Mohammadi, "Control synthesis and ISS stability analysis of a dual-user haptic training system based on S-shaped function," IEEE/ASME Transactions on Mechatronics, vol. 24, no. 4, pp. 1553-1564, 2019. [DOI:10.1109/TMECH.2019.2917448]
13. M. Shahbazi, S. F. Atashzar, H. A. Talebi, and R. V. Patel, "An expertise-oriented training framework for robotics-assisted surgery," in 2014 IEEE international conference on robotics and automation (ICRA), 2014: IEEE, pp. 5902-5907. [DOI:10.1109/ICRA.2014.6907728]
14. F. Liu, A. Lelevé, D. Eberard, and T. Redarce, "A dual-user teleoperation system with online authority adjustment for haptic training," in 2015 37th annual international conference of the IEEE engineering in medicine and biology society (EMBC), 2015: IEEE, pp. 1168-1171. [DOI:10.1109/EMBC.2015.7318574]
15. Z. Lu, P. Huang, P. Dai, Z. Liu, and Z. Meng, "Enhanced transparency dual-user shared control teleoperation architecture with multiple adaptive dominance factors," International Journal of Control, Automation and Systems, vol. 15, no. 5, pp. 2301-2312, 2017. [DOI:10.1007/s12555-016-0467-y]
16. R. Heidari, M. Motaharifar, and H. Taghirad, "Robust Impedance Control for Dual User Haptic Training System," in 2019 7th International Conference on Robotics and Mechatronics (ICRoM), 2019: IEEE, pp. 181-185. [DOI:10.1109/ICRoM48714.2019.9071859]
17. M. Motaharifar, H. D. Taghirad, K. Hashtrudi-Zaad, and S. F. Mohammadi, "Control of Dual-User Haptic Training System With Online Authority Adjustment: An Observer-Based Adaptive Robust Scheme," IEEE Transactions on Control Systems Technology, 2019. [DOI:10.1109/TCST.2019.2946943]
18. N. Ahmidi et al., "A dataset and benchmarks for segmentation and recognition of gestures in robotic surgery," IEEE Transactions on Biomedical Engineering, vol. 64, no. 9, pp. 2025-2041, 2017. [DOI:10.1109/TBME.2016.2647680]
19. C. P. Van Der Vleuten, "The assessment of professional competence: developments, research and practical implications," Advances in Health Sciences Education, vol. 1, no. 1, pp. 41-67, 1996. [DOI:10.1007/BF00596229]
20. J. Martin et al., "Objective structured assessment of technical skill (OSATS) for surgical residents," British journal of surgery, vol. 84, no. 2, pp. 273-278, 1997. [DOI:10.1046/j.1365-2168.1997.02502.x]
21. H. Al Hajj et al., "CATARACTS: Challenge on automatic tool annotation for cataRACT surgery," Medical image analysis, vol. 52, pp. 24-41, 2019. [DOI:10.1016/j.media.2018.11.008]
22. G. S. Guthart and J. K. Salisbury, "The Intuitive/sup TM/telesurgery system: overview and application," in Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No. 00CH37065), 2000, vol. 1: IEEE, pp. 618-621.
23. Z. Lin et al., "Objective skill evaluation for laparoscopic training based on motion analysis," IEEE Transactions on Biomedical Engineering, vol. 60, no. 4, pp. 977-985, 2012. [DOI:10.1109/TBME.2012.2230260]
24. T. Horeman, J. Dankelman, F. W. Jansen, and J. J. van den Dobbelsteen, "Assessment of laparoscopic skills based on force and motion parameters," IEEE Transactions on Biomedical Engineering, vol. 61, no. 3, pp. 805-813, 2013. [DOI:10.1109/TBME.2013.2290052]
25. T. Horeman, S. P. Rodrigues, F. W. Jansen, J. Dankelman, and J. J. van den Dobbelsteen, "Force parameters for skills assessment in laparoscopy," IEEE Transactions on Haptics, vol. 5, no. 4, pp. 312-322, 2011. [DOI:10.1109/TOH.2011.60]
26. K. R. Martin and R. L. Burton, "The phacoemulsification learning curve: per-operative complications in the first 3000 cases of an experienced surgeon," Eye, vol. 14, no. 2, pp. 190-195, 2000. [DOI:10.1038/eye.2000.52]
27. S. Cotin, N. Stylopoulos, M. Ottensmeyer, P. Neumann, D. Rattner, and S. Dawson, "Metrics for laparoscopic skills trainers: The weakest link!," in International conference on medical image computing and computer-assisted intervention, 2002: Springer, pp. 35-43. [DOI:10.1007/3-540-45786-0_5]
28. A. L. Trejos, R. V. Patel, R. A. Malthaner, and C. M. Schlachta, "Development of force-based metrics for skills assessment in minimally invasive surgery," Surgical endoscopy, vol. 28, no. 7, pp. 2106-2119, 2014. [DOI:10.1007/s00464-014-3442-9]
29. A. Zia and I. Essa, "Automated surgical skill assessment in RMIS training," International journal of computer assisted radiology and surgery, vol. 13, no. 5, pp. 731-739, 2018. [DOI:10.1007/s11548-018-1735-5]

Add your comments about this article : Your username or Email:

Send email to the article author

© 2021 All Rights Reserved | Journal of Control

Designed & Developed by : Yektaweb