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Revista de la Facultad de Medicina Humana
versión impresa ISSN 1814-5469versión On-line ISSN 2308-0531
Rev. Fac. Med. Hum. vol.24 no.4 Lima oct./dic. 2024 Epub 31-Oct-2024
http://dx.doi.org/10.25176/rfmh.v24i4.6807
Special Article
Mixed reality in surgical mechatronics: Innovations and challenges in bioengineering education and clinical practice
1 Instituto de Investigaciones en Ciencias Biomédicas (INICIB), Universidad Ricardo Palma, Lima, Peru
2 School of Mechatronics Engineering, Faculty of Engineering, Universidad Ricardo Palma, Lima, Peru
4 Grupo de Investigación en Robótica y Mecatrónica Avanzada (GI-ROMA), Universidad Ricardo Palma, Lima, Peru
Background: .
Mixed reality (MR), a combination of augmented reality (AR) and virtual reality (VR), has emerged as a key tool in surgical mechatronics, improving precision and visualization in clinical procedures
Methods:
This study presents a literature review of recent MR advances from the Scopus database, taking into account its impact on surgery and medical education. Technologies such as Microsoft HoloLens and Magic Leap, as well as neurosurgery and orthopedic simulators, are reviewed.
Results:
MR enhances surgical precision and reduces operating times, with an average decrease from 121.34 to 97.62 minutes. Despite its potential, challenges include discomfort from prolonged device use and low battery autonomy.
Conclusions:
MR has the potential to transform surgery and medical education; however, its widespread adoption will depend on overcoming technological and financial barriers, especially in Latin America, where infrastructure is still limited.
Keywords: Surgery; mechatronics; virtual reality; medical education; bioengineering
INTRODUCTION
Mixed reality (MR) lies between augmented reality (AR) and virtual reality (VR), combining elements of both to offer a more advanced interactive experience. VR creates fully virtual and immersive environments that can engage multiple senses, while AR overlays virtual data onto the real-world environment, without deep interaction 1. In contrast, MR integrates virtual data into the real environment, allowing real-time interaction, providing a more immersive and functional experience 2,3, as shown in Table 1. Devices such as HoloLens enable the visualization of three-dimensional data during surgical procedures without disrupting the workflow, although they face challenges such as the need for specialized software and potential side effects for users 4,5 (Figure 1). Globally, the majority of studies have been conducted in the United States (1883), followed by England (677), Canada (600), Germany (509), and Italy (444), with Peru falling below 100 studies 6. Despite these challenges, MR has the potential to transform surgery and medical education, improving precision and real-time decision-making.
Figure 1 Proposal for future collaborative implementation of brain surgery, utilizing virtual reality glasses to visualize the morphology of the organ. Original contribution.
Table 1 Comparison of mixed reality (MR) technologies in surgery
| Characteristic | Augmented Reality (AR) | Mixed Reality (MR) |
| Interaction | Real-time direct or indirect view of a physical real-world environment enhanced/augmented by computer-generated information (7,8). | It integrates physical and digital environments, allowing continuous interaction between them. It helps design and evaluate how users interact with physical and digital elements simultaneously (9). |
| Devices | Phones, tablets, AR glasses, headsets like HoloLens (10). | Head-mounted display, wearable display devices, monitor-based and projection-based screens (11). |
| Applications | Advertising and commercial, entertainment and education, medicine, and mobile applications for iPhones (12). | Education with integrated learning, collaborative design with virtual models in real environments (11), neurosurgery, maxillofacial surgery, general surgery (13). |
In this context, computer-assisted surgery (CAS) emerges 14,15, integrating mechatronic systems with MR to provide surgeons with training without compromising patient safety 16, as seen in robotic surgery 17, neurosurgery, orthopedics, laparoscopy, endoluminal intervention with flexible robots, the use of medical capsules, and unconnected micro/nano robots, among others, demonstrating significant progress in enhancing precision and minimizing invasiveness 18 (Figure 2). In 2009, Mauro et al. developed an MR neurosurgical microscope for training and intraoperative purposes, with realistic simulation (visual and haptic) for palpation of low-grade gliomas, along with augmented reality stereoscopic visualization of 3D data relevant for safe surgical movements in image-guided interventions 19-21.
Figure 2 (a) Visualization of intraoperative surgery with 3D virtual reality models (22). (b) Laparoscopic simulator with high-fidelity soft tissue representation (23). (c) Mixed reality (MR) navigation system (24).
Other studies have also explored the use of MR in surgical and microsurgical simulation environments. In 2020, Galati et al. proposed a system based on Microsoft HoloLens, a Digital Imaging and Communication in Medicine (DICOM) viewer, and a visualization tool developed in Unity. This system improves the speed and precision of surgeries by displaying real-time information directly in the surgeon's visor, eliminating the need to leave the operating table. However, this approach presents challenges such as increased physical strain, discomfort due to the device's weight, and battery autonomy issues 25. In 2023, Xiang et al. developed an MR framework for microsurgery simulation, combining a surgical microscope with real precision instruments, offering an immersive experience with visual and tactile interaction. This system enables the practice of anastomosis skills and uses vision-based tracking to monitor instruments and artificial blood vessels, as well as to quickly create virtual assets in various microsurgical specialties 26. Also in 2023, Jain et al. explored the use of mixed reality (MR) technology in neurosurgical teaching, given the decline in cadaveric dissections and the need for new learning methods. Three neurosurgeons served as facilitators using the HoloLens 2 device without prior student training. Eight neurosurgery residents evaluated the experience, finding a short learning curve and rating the device as engaging, reliable, and easy to use. Although opinions were mixed on whether MR should replace traditional methods, the study demonstrates that this technology is viable for neurosurgical training 27. These studies highlight the potential of MR to enhance both training and surgical outcomes, though technological challenges remain to be addressed.
APPLICATION IN SURGICAL INNOVATION
MR is gaining traction in surgical education, with several companies heavily investing in this technology (Table 2). Microsoft, through its HoloLens project and Windows Mixed Reality, has developed an MR system that combines high-precision hardware and software. This system has been used in medical, industrial, and educational applications, allowing surgeons to visualize three-dimensional holograms during surgical procedures without disrupting workflow.
This technology improves precision and reduces errors; moreover, it is a pioneer in clinical studies and simulations 28. Magic Leap, on the other hand, has developed light field technology that provides a better sense of fusion between the physical and virtual worlds, achieving greater realism in 3D image projection. This enables real-time medical collaboration and has enhanced training and diagnostics in surgical specialties 29,30. Finally, MetaVision is bringing MR to the end user by commercializing a more affordable device, although it is geared toward the consumer market; this company has popularized MR and facilitated its adoption in medical education and clinical simulation 31.
Table 2 Main features of the leading MR devices
| Device | Main features | Price (USD) |
| HoloLens (28) | Transparent holographic lenses, 2-3 hours battery life in active use, Wi-Fi 802.11ac and Bluetooth 4.1 connectivity, 2MP cameras, 64GB storage. | 3,000 |
| Magic Leap One (28) | 40° FOV, 1280 x 960 resolution per eye, rechargeable battery, Bluetooth 4.2 and Wi-Fi connectivity, 1080p RGB color camera, 64GB SSD storage. | 2,500 |
| Meta 2 (32) | 90° field of view, 2.5K resolution, 9-foot cable for data and power, wired connectivity, 720p RGB camera, 128GB storage. | 1,500 |
In Mexico, the Universidad Nacional Autónoma de México (UNAM) successfully used an innovative lens system to visualize a hologram of the patient and performed the first surgery using MR. The experience gained has led to collaboration with Microsoft on a holographic surgery project involving specialists from 13 countries 33. Additionally, in 2019, Arroyo-Berezowsky et al. conducted a study with 10 residents, where the VR group completed the task in 25.84 minutes, compared to 31.6 minutes for the control group, highlighting that the VR group tended to finish earlier 34. On the other hand, in 2024, García et al. developed VirtualCPR, a virtual reality application for CPR training 35. Finally, in 2016, Medellín-Castillo et al. presented a new 3D digital cephalometry approach with haptic support, which improved precision and reduced errors and variability compared to 2D and 2½D methods, proving to be more intuitive and efficient for dental surgeons 36.
In Brazil, in 2016, da Cruz et al. studied preoperative warm-up with virtual reality simulators and found a significant improvement in surgical performance among medical students with basic laparoscopy experience 37. Additionally, in 2016, de Faria et al. developed an interactive and stereoscopic resource for teaching neuroanatomy, significantly improving student learning compared to traditional teaching methods 38. In Spain, researchers from the Universidad de Málaga demonstrated that virtual reality is a viable and more efficient alternative to 3D-printed models for classifying proximal humerus fractures in pre-surgical planning 39.
In Peru, the situation is different. Although the country has approximately 35 medical schools or faculties in 18 of its 24 provinces, only about 14% of them use virtual reality interfaces 40, and not all employ digital devices or have annual subscriptions for courses such as Physiology, Anatomy, Histology, Surgery, and/or Pathology 41-43. This contrasts with other countries in the region and around the world that are promoting the use of augmented and virtual reality to improve educational processes 44,45. While efforts are being made to incorporate new technologies in line with global developments, such as the use of surgical robots like Da Vinci 46, the current Peruvian context requires an accelerated renewal of medical education systems 47,48. This should go beyond conventional educational objectives and include reforms ranging from the student admission process to organized educational quality. The use of mixed reality (MR) in education in Peru is more common in Physics (15%), Computer Science, and Engineering (around 12%), while disciplines such as Astronomy, Geology, and Earth Sciences have much lower adoption rates (less than 2%). This suggests that technological and scientific areas benefit more from MR, while other fields are still lagging behind in its use (Figure 3).
Figure 4 (a) Concept of 3D light field visualization based on eye-tracking, illustrating the generation and modeling of directional light rays. (b) 3D visualization prototype for medical applications: 3D cardiac computed tomography navigator. Obtained under the CC BY 4.0 license 56.
CONCLUSION
To effectively implement these technologies in Latin America, several factors need to be considered: investment in infrastructure, healthcare personnel training, and adaptation to local needs 49. MR has enormous potential to enhance both medical education and patient treatment 50, especially compared to Europe and North America, where significant increases in surgical efficiency have been observed.
There is a weighted mean difference of 12.31 in skill training capacity 51, along with improvements in educational quality, as the average time of surgical procedures has been reduced to 97.62±35.59 minutes, compared to traditional cadaver-based teaching methods, which have an average time of 121.34±12.17 minutes 52,53.
Despite financial and infrastructural challenges, lessons learned from other regions can guide the successful integration of mixed reality into the Latin American medical field, adapting to its unique context 54-55) (Figure 4).
REFERENCES
1. McKnight RR, Pean CA, Buck JS, Hwang JS, Hsu JR, Pierrie SN. Virtual Reality and Augmented Reality-Translating Surgical Training into Surgical Technique. Curr Rev Musculoskelet Med. 2020;13(6):663-74. doi:10.1007/s12178-020-09667-3 [ Links ]
2. Tepper OM, Rudy HL, Lefkowitz A, Weimer KA, Marks SM, Stern CS, et al. Mixed Reality with HoloLens: Where Virtual Reality Meets Augmented Reality in the Operating Room. Plast Reconstr Surg. 2017;140(5):1066. doi:10.1097/PRS.0000000000003802 [ Links ]
3. Yoon JW, Chen RE, Kim EJ, Akinduro OO, Kerezoudis P, Han PK, et al. Augmented reality for the surgeon: Systematic review. Int J Med Robot. 2018;14(4):e1914. doi:10.1002/rcs.1914 [ Links ]
4. Vervoorn MT, Wulfse M, Doormaal TPCV, Ruurda JP, Kaaij NPV der, Heer LMD. Mixed Reality in Modern Surgical and Interventional Practice: Narrative Review of the Literature. JMIR Serious Games. 2023;11(1):e41297. doi:10.2196/41297 [ Links ]
5. Cornejo J, Cornejo-Aguilar JA, Vargas M, Helguero CG, Milanezi de Andrade R, Torres-Montoya S, et al. Anatomical Engineering and 3D Printing for Surgery and Medical Devices: International Review and Future Exponential Innovations. BioMed Res Int. 2022;2022(1):6797745. doi:10.1155/2022/6797745 [ Links ]
6. Zhang J, Yu N, Wang B, Lv X. Trends in the Use of Augmented Reality, Virtual Reality, and Mixed Reality in Surgical Research: a Global Bibliometric and Visualized Analysis. Indian J Surg. 2022;84(1):52-69. doi:10.1007/s12262-021-03243-w [ Links ]
7. Carmigniani J, Furht B. Augmented Reality: An Overview. En: Furht B, editor. Handbook of Augmented Reality [Internet]. New York, NY: Springer; 2011 [citado el 29 de agosto de 2024]. p. 3-46. doi:10.1007/978-1-4614-0064-6_1 [ Links ]
8. Allcca D, Nacarino A, Sanchez B, Castro R, La-Rosa A, Cornejo J, et al. Mechatronics Bio-Design of Hip Prosthesis using Mechanic of Materials Analysis and Finite Element Method: A Proof of Concept. En: 2024 5th International Conference on Recent Trends in Computer Science and Technology (ICRTCST) [Internet]. 2024 [citado el 31 de agosto de 2024]. p. 438-43. doi:10.1109/ICRTCST61793.2024.10578526 [ Links ]
9. Coutrix C, Nigay L. Mixed reality: a model of mixed interaction. En: Proceedings of the working conference on Advanced visual interfaces [Internet]. New York, NY, USA: Association for Computing Machinery; 2006 [citado el 29 de agosto de 2024]. p. 43-50. (AVI '06). doi:10.1145/1133265.1133274 [ Links ]
10. Liao T. Future directions for mobile augmented reality research: Understanding relationships between augmented reality users, nonusers, content, devices, and industry. Mob Media Commun. 2019;7(1):131-49. doi:10.1177/2050157918792438 [ Links ]
11. Rokhsaritalemi S, Sadeghi-Niaraki A, Choi S-M. A Review on Mixed Reality: Current Trends, Challenges and Prospects. Appl Sci. 2020;10(2):636. doi:10.3390/app10020636 [ Links ]
12. Carmigniani J, Furht B, Anisetti M, Ceravolo P, Damiani E, Ivkovic M. Augmented reality technologies, systems and applications. Multimed Tools Appl. 2011;51(1):341-77. doi:10.1007/s11042-010-0660-6 [ Links ]
13. Moser T, Hohlagschwandtner M, Kormann-Hainzl G, Pölzlbauer S, Wolfartsberger J. Mixed Reality Applications in Industry: Challenges and Research Areas. En: Winkler D, Biffl S, Bergsmann J, editores. Software Quality: The Complexity and Challenges of Software Engineering and Software Quality in the Cloud. Cham: Springer International Publishing; 2019. p. 95-105. doi:10.1007/978-3-030-05767-1_7 [ Links ]
14. Adams L, Krybus W, Meyer-Ebrecht D, Rueger R, Gilsbach JM, Moesges R, et al. Computer-assisted surgery. IEEE Comput Graph Appl. 1990;10(3):43-51. doi:10.1109/38.55152 [ Links ]
15. Cornejo J, Cornejo J, Vargas M, Carvajal M, Perales P, Rodríguez G, et al. SY-MIS Project: Biomedical Design of Endo-Robotic and Laparoscopic Training System for Surgery on the Earth and Space. Emerg Sci J. 2024;8(2):372-93. doi:10.28991/ESJ-2024-08-02-01 [ Links ]
16. Cornejo J, Cornejo-Aguilar JA, Gonzalez C, Sebastian R. Mechanical and Kinematic Design of Surgical Mini Robotic Manipulator used into SP-LAP Multi-DOF Platform for Training and Simulation. En: 2021 IEEE XXVIII International Conference on Electronics, Electrical Engineering and Computing (INTERCON) [Internet]. 2021 [citado el 31 de agosto de 2024]. p. 1-4. doi:10.1109/INTERCON52678.2021.9532965 [ Links ]
17. Cornejo J, Barrera S, Ruiz CAH, Gutierrez F, Casasnovas MO, Kot L, et al. Industrial, Collaborative and Mobile Robotics in Latin America: Review of Mechatronic Technologies for Advanced Automation. Emerg Sci J. 2023;7(4):1430-58. doi:10.28991/ESJ-2023-07-04-025 [ Links ]
18. Dagnino G, Kundrat D. Robot-assistive minimally invasive surgery: trends and future directions. Int J Intell Robot Appl [Internet]. 2024 [citado el 7 de octubre de 2024]; doi:10.1007/s41315-024-00341-2 [ Links ]
19. Cornejo J, Cornejo-Aguilar JA, Sebastian R, Perales P, Gonzalez C, Vargas M, et al. Mechanical Design of a Novel Surgical Laparoscopic Simulator for Telemedicine Assistance and Physician Training during Aerospace Applications. En: 2021 IEEE 3rd Eurasia Conference on Biomedical Engineering, Healthcare and Sustainability (ECBIOS) [Internet]. 2021 [citado el 31 de agosto de 2024]. p. 53-6. doi:10.1109/ECBIOS51820.2021.9510753 [ Links ]
20. Cornejo J, Perales-Villarroel JP, Sebastian R, Cornejo-Aguilar JA. Conceptual Design of Space Biosurgeon for Robotic Surgery and Aerospace Medicine. En: 2020 IEEE ANDESCON [Internet]. 2020 [citado el 31 de agosto de 2024]. p. 1-6. doi:10.1109/ANDESCON50619.2020.9272122 [ Links ]
21. De Mauro A, Raczkowsky J, Halatsch ME, Wörn H. Mixed Reality Neurosurgical Microscope for Training and Intra-operative Purposes. En: Shumaker R, editor. Virtual and Mixed Reality [Internet]. Berlin, Heidelberg: Springer Berlin Heidelberg; 2009 [citado el 20 de agosto de 2024]. p. 542-9. (Lecture Notes in Computer Science; vol. 5622). doi:10.1007/978-3-642-02771-0_60 [ Links ]
22. Ujiie H, Chiba R, Yamaguchi A, Nomura S, Shiiya H, Fujiwara-Kuroda A, et al. Developing a Virtual Reality Simulation System for Preoperative Planning of Robotic-Assisted Thoracic Surgery. J Clin Med. 2024;13(2):611. doi:10.3390/jcm13020611 [ Links ]
23. Deng Z, Xiang N, Pan J. State of the Art in Immersive Interactive Technologies for Surgery Simulation: A Review and Prospective. Bioengineering. 2023;10(12):1346. doi:10.3390/bioengineering10121346 [ Links ]
24. Lin Z, Lei C, Yang L. Modern Image-Guided Surgery: A Narrative Review of Medical Image Processing and Visualization. Sensors. 2023;23(24):9872. doi:10.3390/s23249872 [ Links ]
25. Galati R, Simone M, Barile G, De Luca R, Cartanese C, Grassi G. Experimental Setup Employed in the Operating Room Based on Virtual and Mixed Reality: Analysis of Pros and Cons in Open Abdomen Surgery. J Healthc Eng. 2020;2020(1):8851964. doi:10.1155/2020/8851964 [ Links ]
26. Xiang N, Liang H-N, Yu L, Yang X, Zhang JJ. A mixed reality framework for microsurgery simulation with visual-tactile perception. Vis Comput. 2023;39(8):3661-73. doi:10.1007/s00371-023-02964-1 [ Links ]
27. Jain S, Timofeev I, Kirollos RW, Helmy A. Use of Mixed Reality in Neurosurgery Training: A Single Centre Experience. World Neurosurg. 2023;176:e68-76. doi:10.1016/j.wneu.2023.04.107 [ Links ]
28. Palumbo A. Microsoft HoloLens 2 in Medical and Healthcare Context: State of the Art and Future Prospects. Sensors. 2022;22(20). doi:10.3390/s22207709 [ Links ]
29. Cornejo J, Cornejo-Aguilar JA, Palomares R. Biomedik Surgeon: Surgical Robotic System for Training and Simulation by Medical Students in Peru. En: 2019 International Conference on Control of Dynamical and Aerospace Systems (XPOTRON) [Internet]. 2019 [citado el 31 de agosto de 2024]. p. 1-4. doi:10.1109/XPOTRON.2019.8705717 [ Links ]
30. Zari G, Condino S, Cutolo F, Ferrari V. Magic Leap 1 versus Microsoft HoloLens 2 for the Visualization of 3D Content Obtained from Radiological Images. Sensors. 2023;23(6):3040. doi:10.3390/s23063040 [ Links ]
31. Westermeier F, Brübach L, Wienrich C, Latoschik ME. Assessing Depth Perception in VR and Video See-Through AR: A Comparison on Distance Judgment, Performance, and Preference. IEEE Trans Vis Comput Graph. 2024;30(5):2140-50. doi:10.1109/TVCG.2024.3372061 [ Links ]
32. Anaya-Sánchez R, Rejón-Guardia F, Molinillo S. Impact of virtual reality experiences on destination image and visit intentions: the moderating effects of immersion, destination familiarity and sickness. Int J Contemp Hosp Manag [Internet]. 2024 [citado el 31 de agosto de 2024];ahead-of-print(ahead-of-print). doi:10.1108/IJCHM-09-2023-1488 [ Links ]
33. Zaragoza Pérez R, Cuevas Escudero AL. Realidad aumentada en la enseñanza. RDU UNAM [Internet]. 2020 [citado el 31 de agosto de 2024]; doi:10.22201/cuaieed.16076079e.2020.21.6.9 [ Links ]
34. Arroyo-Berezowsky C, Jorba-Elguero P, Altamirano-Cruz MA, Quinzaños-Fresnedo J. Usefulness of immersive virtual reality simulation during femoral nail application in an orthopedic fracture skills course. J Musculoskelet Surg Res. 2019;3:326. doi:10.4103/jmsr.jmsr_78_19 [ Links ]
35. De Jesus Encarnacion Ramirez M, Chmutin G, Nurmukhametov R, Soto GR, Kannan S, Piavchenko G, et al. Integrating Augmented Reality in Spine Surgery: Redefining Precision with New Technologies. Brain Sci. 2024;14(7):645. doi:10.3390/brainsci14070645 [ Links ]
36. Medellín-Castillo HI, Govea-Valladares EH, Pérez-Guerrero CN, Gil-Valladares J, Lim T, Ritchie JM. The evaluation of a novel haptic-enabled virtual reality approach for computer-aided cephalometry. Comput Methods Programs Biomed. 2016;130:46-53. doi:10.1016/j.cmpb.2016.03.014 [ Links ]
37. da Cruz JAS, dos Reis ST, Cunha Frati RM, Duarte RJ, Nguyen H, Srougi M, et al. Does Warm-Up Training in a Virtual Reality Simulator Improve Surgical Performance? A Prospective Randomized Analysis. J Surg Educ. 2016;73(6):974-8. doi:10.1016/j.jsurg.2016.04.020 [ Links ]
38. de Faria JWV, Teixeira MJ, de Moura Sousa Júnior L, Otoch JP, Figueiredo EG. Virtual and stereoscopic anatomy: when virtual reality meets medical education. J Neurosurg. 2016;125(5):1105-11. doi:10.3171/2015.8.JNS141563 [ Links ]
39. Almirón Santa-Bárbara R, García Rivera F, Lamb M, Víquez Da-Silva R, Gutiérrez Bedmar M. New technologies for the classification of proximal humeral fractures: Comparison between Virtual Reality and 3D printed models-a randomised controlled trial. Virtual Real. 2023;27(3):1623-34. doi:10.1007/s10055-023-00757-4 [ Links ]
40. Morales-Mere J, Chessa JJ, Palomares R, Cornejo J. Mixed Reality System for Education and Innovation in Prehospital Interventions at Peruvian Fire Department. En: 2020 IEEE XXVII International Conference on Electronics, Electrical Engineering and Computing (INTERCON) [Internet]. 2020 [citado el 1 de septiembre de 2024]. p. 1-4. doi:10.1109/INTERCON50315.2020.9220259 [ Links ]
41. Wilson AB, Miller CH, Klein BA, Taylor MA, Goodwin M, Boyle EK, et al. A meta-analysis of anatomy laboratory pedagogies. Clin Anat. 2018;31(1):122-33. doi:10.1002/ca.22934 [ Links ]
42. Cornejo-Aguilar JA, Cornejo J, Vargas M, Sebastian R. The revolution of robotic surgery in latin america and the future implementation in the healthcare system of Peru: La revolución de la cirugía robótica en latino américa y la futura implementación en el sistema de salud del perú. Rev Fac Med Humana. 2019;19(1):5. doi:10.25176/RFMH.v19.n1.1800 [ Links ]
43. Cornejo J, Cornejo Aguilar JA, Perales Villarroel JP. INTERNATIONAL INNOVATIONS IN MEDICAL ROBOTICS TO IMPROVE THE PATIENT MANAGEMENT IN PERU: INNOVACIONES INTERNACIONALES EN ROBÓTICA MÉDICA PARA MEJORAR EL MANEJO DEL PACIENTE EN PERÚ. Rev Fac Med Humana. 2019;19(4):1. doi:10.25176/RFMH.v19i4.2349 [ Links ]
44. Mendoza GAA, Lewis F, Plante P, Brassard C. Estado del arte sobre el uso de la realidad virtual, la realidad augmentada y el video 360° en educación superior. Edutec Rev Electrónica Tecnol Educ. 2023;(84):35-51. doi:10.21556/edutec.2023.84.2769 [ Links ]
45. Cornejo J, Vargas M, Cornejo-Aguilar JA. Robotics and Biomedical Innovative Applications in Public Health during the COVID-19 Pandemic: Aplicaciones Innovadoras De La Robótica Y Biomédica En La Salud Pública Durante La Pandemia Del COVID-19. Rev Fac Med Humana [Internet]. 2020 [citado el 2 de septiembre de 2024];20(4). doi:10.25176/RFMH.v20i4.3042 [ Links ]
46. Clínica Internacional adquiere el primer robot quirúrgico en el Perú | empresas | breca | cirugías | medicina | cirujanos | Intuitive Surgical | ECONOMIA | GESTIÓN [Internet]. [citado el 7 de octubre de 2024]. Disponible en: https://gestion.pe/economia/empresas/clinica-internacional-adquiere-el-primer-robot-quirurgico-en-el-peru-empresas-breca-cirugias-medicina-cirujanos-intuitive-surgical-noticia/#google_vignette [ Links ]
47. Vargas M, Cornejo J, De La Cruz-Vargas JA. Health without Borders: INICIB-URP leading Medical Education through Bioengineering and Mechatronic Technologies: Salud sin Fronteras: INICIB-URP liderando la Educación Médica a través de Bioingeniería y Tecnologías Mecatrónicas. Rev Fac Med Humana. 2024;24(3):07-11. doi:10.25176/RFMH.v24i3.6701 [ Links ]
48. Vargas M, Cornejo J, Correa-López LE. Ingeniería biomédica: la revolución tecnológica para el futuro del sistema de salud peruano. Rev Fac Med Humana [Internet]. 2017 [citado el 2 de septiembre de 2024];16(2). doi:10.25176/RFMH.v16.n3.659 [ Links ]
49. Caballero-Garriazo JA, Rojas-Huacanca JR, Sánchez-Castro A, Lázaro-Aguirre AF. Systematic review on the application of Virtual Reality in University Education. Rev Electrónica Educ. 2023;27(3):1-18. doi:10.15359/ree.27-3.17271 [ Links ]
50. Morimoto T, Kobayashi T, Hirata H, Otani K, Sugimoto M, Tsukamoto M, et al. XR (Extended Reality: Virtual Reality, Augmented Reality, Mixed Reality) Technology in Spine Medicine: Status Quo and Quo Vadis. J Clin Med. 2022;11(2):470. doi:10.3390/jcm11020470 [ Links ]
51. Zhang R, Jin X, Liu M, Tong HY. The Effectiveness of Augmented Reality/Mixed Reality in Medical Education: A Meta- Analysis [Internet]. 2024 [citado el 30 de agosto de 2024]. doi:10.21203/rs.3.rs-4549366/v1 [ Links ]
52. Wu Q, Wang Y, Lu L, Chen Y, Long H, Wang J. Virtual Simulation in Undergraduate Medical Education: A Scoping Review of Recent Practice. Front Med [Internet]. 2022 [citado el 30 de agosto de 2024];9. doi:10.3389/fmed.2022.855403 [ Links ]
53. Sadek O, Baldwin F, Gray R, Khayyat N, Fotis T. Impact of Virtual and Augmented Reality on Quality of Medical Education During the COVID-19 Pandemic: A Systematic Review. J Grad Med Educ. 2023;15(3):328-38. doi:10.4300/JGME-D-22-00594.1 [ Links ]
54. Martel Cervantes C, Sandoval C, Palomares R, Borja Arroyo J, Murillo Manrique M, Cornejo J. BIOMEDICAL ANTHROPOMETRIC EVALUATION AND CONCEPTUAL MECHANICAL DESIGN OF A ROBOTIC SYSTEM FOR LOWER LIMBS PASSIVE-REHABILITATION ON POST-STROKE PATIENTS. Revista de la Facultad de Medicina Humana. 2024 Apr 1;24(2). doi: 10.25176/rfmh.v24i2.6550 [ Links ]
55. Sandoval C, Martel C, Palomares R, Arroyo JB, Manrique MFM, Cornejo J. Conceptual mechatronic design of ankle-foot exoskeleton system for assisted rehabilitation of pediatric patients with spastic cerebral palsy. In: 2023 IEEE MIT Undergraduate Research Technology Conference (URTC). IEEE; 2023. doi: 10.1109/URTC60662.2023.10534922 [ Links ]
56. Kang D, Choi JH, Hwang H. Autostereoscopic 3D display system for 3D medical images. Applied Sciences. 2022 Apr 24;12(9):4288. doi: 10.3390/app12094288 [ Links ]
8Article published by the Journal of the faculty of Human Medicine of the Ricardo Palma University. It is an open access article, dis-tributed under the terms of the Creatvie Commons license: Creative Commons At-tribution 4.0 International, CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/), that allows non-commercial use, distribution and reproduction in any medium, provided that the original work is duly cited. For commercial use, please contact revista.medicina@urp.edu.pe.
Received: September 01, 2024; Accepted: October 08, 2024
Este es un artículo publicado en acceso abierto bajo una licencia Creative Commons
