Cover
Vol. 19 No. 2 (2023)

Published: December 31, 2023

Pages: 138-144

Review Article

Issues and Research Fields of Medical Robotics: A Review

Sarah Sabeeh 1 Israa S. Al-Furati 2
1Computers Engineering Department, University of Basrah ,Basrah ,Iraq
2Electrical Engineering Department, University of Basrah, Basrah, Iraq
History
  • Received: January 19, 2023
  • Revised: April 28, 2023
  • Accepted: April 28, 2023
  • Available Online: August 14, 2023
DOI

https://doi.org/10.37917/ijeee.19.2.16

Abstract

The goal for collaborative robots has always driven advancements in robotic technology, especially in the manufacturing sector. However, this is not the case in service sectors, especially in the health sector. Thus, this lack of focus has now opened more room for the design and development of service robots that can be used in the health sector to help patients with ailments, cognitive problems, and disabilities. There is currently a global effort towards the development of new products and the use of robotic medical devices and computer-assisted systems. However, the major problem has been the lack of a thorough and systematic review of robotic research into disease and epidemiology, especially from a technology perspective. Also, medical robots are increasingly being used in healthcare to perform a variety of functions that improve patient care. This scoping review is aimed at discovering the types of robots used in healthcare and where they are deployed. Moreover, the current study is an overview of various forms of robotic technology and its uses the healthcare industry. The considered technologies are the products of a partnership between the healthcare sector and academia. They demonstrate the research and testing that are necessary for the service of robot development before they can be employed in practical applications and service scenarios. The discussion also focused on the upcoming research areas in robotic systems as well as some important technologies necessary for human-robot collaboration, such as wireless sensor networks, big data, and artificial intelligence.

Keywords

References

  1. J. Holland, L. Kingston, C. McCarthy, E. Armstrong, P. O. Dwyer, F. Merz, and M. McConnell, “Service robots in the healthcare sector,” Robotics, vol. 10, no. 1, p. 47, 2021.
  2. R. Maity, R. Mishra, and P. K. Pattnaik, “A review of flying robot applications in healthcare,” Smart Healthc. Anal. State Art, pp. 103–111, 2022.
  3. S. Matsumoto, S. Moharana, N. Devanagondi, L. C. Oyama, and L. D. Riek, “Iris: A low-cost telemedicine robot to support healthcare safety and equity during a pandemic,” in International Conference on Pervasive Computing Technologies for Healthcare, pp. 113–133, 2022.
  4. I. S. A. Alfurati and A. T. Rashid, “design and imple- mentation of an indoor robot positioning system using led array and ldr sensor,” Journal of Engineering Science and Technology, vol. 16, no. 2, April 2021.
  5. D. Sharma, A. Z. B. Nawab, and M. Alam, “Integrating m-health with iomt to counter covid-19 in computational intelligence methods in covid-19: Surveillance, preven- tion, prediction and diagnosis,” Springer, pp. 373–396, 2021.
  6. Z. H. Khan, A. Siddique, and C. W. Lee, “Robotics utilization for healthcare digitization in global covid- 19 management,” Int. J. Environ. Res. Public Health, vol. 17, no. 11, p. 3819, 2020.
  7. Z. Zeng, P.-J. Chen, and A. A. Lew, “From high-touch to high-tech: Covid-19 drives robotics adoption,” Tour. Geogr., vol. 22, no. 3, pp. 724–734, 2020.
  8. I. S. A. Alfurati, B. A. Issa, O. T. Rashid, and A. T. Rashid, “Design and construction a falling water digi- tal display system,” International Journal of Computer Applications, p. 975, 2019.
  9. A. J. Hung, J. Chen, Z. Che, T. Nilanon, A. Jarc, M. Ti- tus, P. J. Oh, I. S. Gill, and Y. Liu, “Utilizing machine learning and automated performance metrics to evaluate robot-assisted radical prostatectomy performance and predict outcomes,” J. Endourol, vol. 32, no. 5, pp. 438– 444, 2018.
  10. A. Amin, A. Vartanian, N. Poladian, A. Voloshko, A. Yegiazaryan, A. L. Al-Kassir, and V. Venketaraman, “Root causes of fungal coinfections in covid-19 infected patients,” Infect. Dis. Rep., vol. 13, no. 4, pp. 1018–1035, 2021.
  11. S. Kim, J. Kim, F. Badu-Baiden, M. Giroux, and Y. Choi, “Preference for robot service or human service in hotels impacts of the covid-19 pandemic,” Int. J. Hosp. Manag., vol. 93, p. 102795, 2021. 143 | Sabeeh & Alfurati
  12. I. S. A. Alfurati, A. Rashid, and A. Al-Ibadi, “Ir sensors array for robots localization using k means clustering algorithm,” International Journal of Simulation Systems, Science & Technology, vol. 12, no. 1, pp. 94–105, March ,2019.
  13. S. Raje, N. Reddy, H. Jerbi, P. Randhawa, G. Tsaramir- sis, N. V. Shrivas, A. Pavlopoulou, M. Stojmenovic, and D. Piromalis, “Applications of healthcare robots in com- bating the covid-19 pandemic,” Appl. bionics Biomech., vol. 2021, pp. 3327–3336, 2021.
  14. R. Taylor, A. Menciassi, G. Fichtinger, P. Fiorini, and P. Dario, “Medical robotics and computer-integrated surgery,” in Springer handbook of robotics, Springer, pp. 1657–1684, 2016.
  15. F. Dworschak, S. Dietze, M. Wittmann, B. Schleich, and S. Wartzack, “Reinforcement learning for engineer- ing design automation,” Adv. Eng. Informatics, vol. 52, p. 101612, 2022.
  16. K. Chinzei, “Safety of surgical robots and iec 80601-2- 77: the first international standard for surgical robots,” Acta Polytech. Hungarica, vol. 16, no. 8, pp. 171–184, 2019.
  17. I. S. A. Alfurati and A. T. Rashid, “Performance compar- ison of three types of sensor matrices for indoor multi- robot localization,” International Journal of Computer Applications, vol. 181, no. 26, pp. 22–29, 2018.
  18. F. Rubio, F. Valero, and C. Llopis-Albertt, “A review of mobile robots: Concepts, methods, theoretical frame- work and applications,” Int. J. Adv. Robot. Syst., vol. 16, no. 2, p. 1729881419839596, 2019.
  19. P. Ponce, E. A. Mart´ınez-Rios, J. I. Mendez, A. Molina, and R. A. Ramirez-Mendoza, “Health: Human-machine interaction, medical robotics, patient rehabilitation,” in Biometry, CRC Press, pp. 110–131, 2022.
  20. I. S. A. Alfurati and A. T. Rashid, “Robotics path plan- ning algorithms using low-cost ir sensor,” Iraqi Journal for Electrical and Electronic Engineering, 2020.
  21. I. S. A. Alfurati and A. T. Rashid, “Practical implemen- tation of an indoor robot localization and identification system using an array of anchor nodes,” Iraqi Journal for Electrical & Electronic Engineering, vol. 16, no. 1, 2020.
  22. B. Tao, Y. Feng, X. Fan, M. Zhuang, X. Chen, F. Wang, and Y. Wu, “Accuracy of dental implant surgery using dynamic navigation and robotic systems: An in vitro study,” J. Dent., p. 104170, 2022.
  23. S.-Q. Li, W.-L. Guo, H. Liu, T. Wang, Y.-Y. Zhou, T. Yu, C.-Y. Wang, Y.-M. Yang, N.-S. Zhong, N.-F. Zhang, and S.-Y. Li, “Clinical application of an intelligent oropha- ryngeal swab robot: Implication for the covid-19 pan- demic,” Eur. Respir. J, vol. 56, no. 2, 2020.
  24. I. S. A. Alfurati and A. Rashid, “Design and implementa- tion an indoor robot localization system using minimum bounded circle algorithm,” 8th International Confer- ence on Modeling Simulation and Applied Optimization (ICMSAO), pp. 1–6, April, 2019.
  25. R. Dey, S. Khan, and B. Saha, “A novel functional ap- proach toward identifying definitive drug targets,” Curr. Med. Chem., vol. 14, no. 22, pp. 2380–2392, 2007.
  26. K. Cresswell, S. Ramalingam, and A. Sheikh, “Can robots improve testing capacity for sars-cov-2,” J. Med. Internet Res., vol. 22, no. 8, 2020.
  27. K. Takahashi, H. Mutsuzaki, K. Yoshikawa, S. Ya- mamoto, K. Koseki, R. Takeuchi, Y. Mataki, and N. Iwasaki, “Robot-assisted ankle rehabilitation using the hybrid assistive limb for children after equinus surgery: A report of two cases,” Pediatr. Rep., vol. 14, no. 3, pp. 338–351, 2022.
  28. P. Sparwasse, M. P. Brandt, M. Haack, R. Dotzauer, K. Boehm, M. K. Gheith, R. Mager, W. Jager, A. Ziebart, T. Hofner, I. Tsaur, A. Haferkamp, and H. Borgmann, “Robotic surgery can be safely performed for patients and healthcare workers during covid-19 pandemic,” Int. J. Med. Robot. Comput. Assist. Surg, vol. 17, no. 4, 2021.
  29. I. S. A. Alfurati, B. A. Issa, H. M. Amer, and A. I. Hus- sein, “Developing a wristband to monitor heartbeat and temperature using internet of things (iot).,” International Journal of Advances in Engineering and Management (IJAEM), vol. 3, no. 3, pp. 1111–1120, 2021.
  30. I. S. A. AL-Forati and A. Rashid, “Design of high pre- cision radix-8 maf unit with reduced latency,” In 2020 International Congress on Human-Computer Interac- tion, Optimization and Robotic Applications (HORA), pp. 1–6, 2020, June.
  31. S. F. Atashzar, J. Carriere, and M. Tavakoli, “How can intelligent robots and smart mechatronic modules facili- tate remote assessment, assistance, and rehabilitation for isolated adults with neuro-musculoskeletal conditions,” Front. Robot. AI, vol. 32, no. 11, pp. 987–993, 2017.
  32. B. A. Issa and I. S. A. Alfurati, “High precision binary coded decimal (bcd) unit for 128-bit addition,” In 2020 144 | Sabeeh & Alfurati International Conference on Electrical, Communication, and Computer Engineering (ICECCE), pp. 1–5, 2020, June).
  33. F. K. A. Assfor, I. S. Al-Furati, and A. T. Rashed, “Vedic- based squarers with high performance,” Indonesian Jour- nal of Electrical Engineering and Informatics (IJEEI), vol. 9, no. 1, pp. 163–172, 2021.
  34. L. Aymerich-Franch and I. Ferrer, “Analyzing the role of social robots during the covid-19 pandemic,” Technol. Soc., p. 101993, 2022.
  35. S. Sumartojo and D. Lugli, “Lively robots: Robotic technologies in covid-19,” Soc. Cult. Geogr, vol. 23, no. 9, pp. 1220–1237, 2022.
  36. I. S. A. Alfurati and O. T. Rashid, “Smart navigation with static polygons and dynamic robots,” Iraqi Journal for Electrical And Electronic Engineering, vol. 17, no. 1, pp. 987–993, 2021.
  37. E. Iadanza, G. Pasqua, D. Piaggio, C. Caputo, M. Gher- ardelli, and L. Pecchia, “A robotic arm for safe and accu- rate control of biomedical equipment during covid-19,” Health Technol. (Berl), pp. 1–16, 2023.
  38. A. Mirbagheri, F. Farahmand, and A. Ahmadian, “Medi- cal robotics: State-of-the-art applications and research challenges,” Int. J. Healthc. Inf. Syst. Informatics, vol. 8, no. 2, pp. 1–14, 2013.
  39. H. Morohashi, K. Hakamada, T. Kanno, K. Kawashima, H. Akasaka, Y. Ebihara, E. Oki, S. Hirano, and M. Mori, “Social implementation of a remote surgery system in japan: a field experiment using a newly developed sur- gical robot via a commercial network,” Surg. Today, vol. 52, no. 4, pp. 705–714, 2022.
  40. S. Miyachi, Y. Nagano, R. Kawaguchi, T. Ohshima, and H. Tadauchi, “Remote surgery using a neuroendovascu- lar intervention support robot equipped with a sensing function: experimental verification,” Asian J. Neurosurg, vol. 16, no. 2, p. 363, 2021.
  41. I. S. A. Alfurati and A. I. AL-Mayoof, “Design and im- plementation of an injury detection system for corona tracker,” Iraqi Journal for Electrical and Electronic En- gineering, vol. 18, no. 2, 2022.
  42. J. Bacik, P. Tkac, L. Hric, S. Alexovic, K. Kyslan, R. Olexa, and D. Perdukova, “Phollower—the universal autonomous mobile robot for industry and civil environ- ments with covid-19 germicide addon meeting safety requirements,” Appl. Sci., vol. 10, no. 21, p. 7682, 2020.
  43. M. Guettari, I. Gharbi, and S. Hamza, “Uvc disinfection robot,” Environ. Sci. Pollut. Res., vol. 98, pp. 434–441, 2020.
  44. I. S. A. Alfurati, A. Rashid, and F. Al-Assfor, “An effi- cient mathematical approach for an indoor robot localiza- tion system,” Iraqi Journal for Electrical and Electronic Engineering, vol. 15, no. 2, pp. 61–70, 2019, December.
  45. M. A. V. J. Muthugala, S. M. B. P. Samarakoon, M. M. Rayguru, B. Ramalingam, and M. R. Elara, “Wall- following behavior for a disinfection robot using type 1 and type 2 fuzzy logic systems,” Sensors, vol. 20, no. 16, p. 4445, 2020.
  46. I. S. A. Alfurati, F. K. Al-Assfor, and A. K. A. Zahra, “Design and implementation of a low-cost weather sta- tions meter,” In Proceedings of Seventh International Congress on Information and Communication Technol- ogy: ICICT, vol. 3, pp. 167–175, 2022, July.
  47. S. Ahir, D. Telavane, and R. Thomas, “The impact of artificial intelligence, blockchain, big data and evolving technologies in coronavirus disease-2019 (covid-19) cur- tailment,,” in 2020 International Conference on Smart Electronics and Communication (ICOSEC), pp. 113– 120, 2020.