Technological Advancements and Elucidation Gadgets for Healthcare Applications: An Exhaustive Methodological Review-Part-II (Robotics, Drones, 3D-Printing, Internet of Things, Virtual/Augmented and Mixed Reality)
Abstract
:1. Introduction
2. Disrupting Technologies
2.1. Robotics
- (A)
- Surgical Robots—Surgical robots offer high-definition 3-D view capabilities promoting the deployment of robots in “minimally invasive” Complicated Robotic surgeries—Da Vinci Surgical System is one such robotic laparoscopic surgical platform in the United States since 2000. Today, many Global Big Wig companies such as Stryker, Globus Medical, Johnson & Johnson, Siemens Stereotaxis, Smith & Nephew, Mazor Robotics, Auris Health, Intuitive Surgical, Zimmer Biomet, and Medtronic, etc., have developed surgical robots [11] and highlighted the utility of robotics in surgical systems, laparoscopy surgery and tele-rounding robots [12], robotic rehabilitation [13] and dentistry applications, etc.
- (B)
- (C)
- Pharmacy automation robots—for dispensing pharmaceuticals (medicines) at high speed in any medical environment.
- (D)
- Disinfection robots—Pulsed ultraviolet light-based robots disinfect the entire room in a few minutes to prevent the spread of infections [16].
- (E)
- Companion robots—‘Care bots’ to engage with patients emotionally.
- (F)
- Caring robots—Humanoid Robots for transferring aged people from the bed to the wheelchair and back [17].
- (G)
- Tele-presence robots—Tele-operated robots allow healthcare people to work safely from infectious patients: For example, Da-Vinci Robot [18].
- (H)
- Wheeled robots—Mobile robots to move in an environment instead of remaining fixed [19].
- (I)
- Flying mobile robots—Flies like Aerial drones—Quad copters category.
- (J)
- Legged robots—Contain articulated legs to provide locomotion on the ground.
- (K)
- Wearable robots—Wearables to measure body signals and augment human capabilities.
2.2. Drones
2.3. Three Dimensional Printing
- (A)
- Production of new medical products → Manufacturers of medical tools and product companies adopted 3D-printing technology to accurately fabricate prototypes of brand new medical devices and surgical instruments.
- (B)
- Tissue Engineering and 3D-printed organs (bio-printing) → Today, researchers of bio-printing are recreating precisely shaped and geometrically sized synthetic blood vessels (and organs on demand)—totally eliminating the need for autografts in the future. One typical scenario depicted a 3D-printed anatomical model of a hand depicted (Figure 5) with skin grafted as well.
- (C)
- Economically feasible prostheses → 3D-printing technology is playing an optimally promotable role to produce prosthesis sockets for hundreds and thousands of people deprived of access to prosthesis treatments due to financial barriers.
- (D)
- Timely insoles/orthoses → 3D-printing technology erased delays associated in patient-specific insoles and orthoses to ensure improved physical therapies, etc.
2.4. IoT
- (A)
- For patients → plenty of wireless connected wearable devices such as blood pressure monitoring devices, heart rate monitoring cuffs, glucometers for monitoring insulin levels, oxygen level monitoring devices, calorie counters, steps counters, pace makers, exercise checkers, blood pressure variation monitors, and many types of fitness bands to track the health conditions of aged people, heart patients, and many other bedridden diseased patients—such that even the slightest deviations in the routine course of activities immediately alerts family members and healthcare providers to save their lives.
- (B)
- For doctors → With the aid of IoT-based wearable devices, doctors and physicians continuously track patients’ health status more effectively and formulate timely treatment plans, ensuring the safety of patient’s lives.
- (C)
- For hospitals → Almost all IoT-based medical equipment, such as wheelchairs, patient monitors, ventilators, defibrillators, nebulizers, oxygen concentrators, infusion pumps and sterilizers, hygiene monitoring devices, humidity and temperature monitoring equipment, etc., are tagged with sensors to ensure the continuous tracking of real time patient location and data.
- (D)
- For health insurance companies → IoT devices created a transparent environment between insurers and customers with regards to pricing, handling claims, underwriting, drafting, and risk assessment procedures to ensure adequate visibility behind all decisions involved. Further health insurance companies are able to eradicate fraud claims based on the data leveraged from intelligent IoT devices and equipment.
2.5. VR/AR/MR (HoloLens)
- (A)
- Surgical training → Medicos, doctors, and surgeons can be trained to perform complex operations with zero surgical errors.
- (B)
- Robotic surgeries → Surgeons equipped with VR technology can perform highly precise operations with the help of robotic devices.
- (C)
- Anxiety and depression treatments → VR Technology is helpful for patients to overcome phobias and stress-induced disorders by resorting to meditations and relaxation treatments, etc.
- (D)
- Hospital navigations → AR-based navigational and way finding tools (Maps) are helpful in locating hospitals, pharmacies, and healthcare centres.
- (E)
- Personalized treatment to patients → VR and MR technologies are helpful to doctors in explaining the surgical procedures and post recovery steps to the patients more elaborately.
- (F)
- AR powered medical education → With AR technology, doctors and surgeons can generate scenario-based 3D representations, ruling out the visualization-based guess works.
- (G)
- Intravenous assistance and vein detection → Doctors and nurses can use handheld augmented reality (AR) devices equipped with laser technology to look “through patient’s skin” and deep into their veins to draw the blood.
- (H)
- Defibrillator station way-finding → AR Technology helps patients to detect defibrillator stations in the case of emergency situations.
- (I)
- Smart hospital automation → Smart hospital buildings use AR technology for navigational purposes, linking building models with real time sensors.
- (J)
- Data visualization/body mapping and interactive patient information → AR technology immediately points out the problematic points on the human body with relevant statistical data—with the help of smart glasses connected to the smart-phone.
3. Future Scope and Challenges
- (A)
- Investigations are deemed essential to measure the effectiveness of robotics’ use cases in healthcare services, and pricings relevant to robotic surgeries must be reduced; further training the medical staff involved in using robots is another big challenge. On the other hand, patient’s safety, confidentiality, and social attitude towards undergoing treatment with robots are a few addressable challenges.
- (B)
- The typical usage of drones in the healthcare system suffers from many practical limitations, such as short battery life, low speed of operation, low payload carrying capabilities, improper operations in adverse weather conditions, lack of trained drone pilots, security breaches, social acceptance issues, and technological glitches, etc. The increasing number of no-fly zones in some countries pose limitations on using drones to the line-of-sight distance of the operators—drones are not immune to hijacking, hence their flight is not as secure as it is imagined to be.
- (C)
- Despite the significance of IoT in medical imaging, the utility of IoT systems in the healthcare sector is bundled with challenges such as complications in large scale dynamic networking, node mobility management, data completeness, data compression, data security, and accurate reproduction of data, etc.; IoT devices are not up to the mark in performing real time monitoring efficiently.
- (D)
- Though 3D-printing turned out to be a boon for the medical community and healthcare sector, different parts produced by the 3D-printers exhibit variations in geometry and mechanical properties due to the differences in type (and quality) of material, software, calibration, and equipment. On the other hand, the non-eco-friendly process of 3D-printing and materials’ scarcity for 3D-printing are few additional challenges to be addressed.
- (E)
- Though VR/AR/MR technologies channelled a great revolution in the healthcare sector, they carry with them plenty of challenges, such as the heaviness of equipment, inconvenience in usage, discomfort and distraction of wearable devices, and limited battery life, and latency parameters involved in the audio and video signals produce a severe impact in the case of surgeries. On the other hand, there is data privacy, content compatibility, awareness, and portability. The lack of trained operators is a biggest challenge to be addressed.
4. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Tan, S.Y.; Taeihagh, A. Governing the adoption of robotics and autonomous systems in long-term care in Singapore. Policy Soc. 2021, 40, 211–231. [Google Scholar] [CrossRef]
- Carter-Templeton, H. Robotics in Nursing: A Bibliometric Analysis. J. Nurs. Scholarsh. 2018, 50, 582–589. [Google Scholar] [CrossRef] [Green Version]
- Poljak, M.; Šterbenc, A. Use of drones in clinical microbiology and infectious diseases: Current status, challenges and barriers. Clin. Microbiol. Infect. 2020, 26, 425–430. [Google Scholar] [CrossRef] [PubMed]
- Chehri, A.; Mouftah, H.; Jeon, G. A Smart Network Architecture for e-Health Applications. In Intelligent Interactive Multimedia Systems and Services. Smart Innovation, Systems and Technologies; Tsihrintzis, G.A., Damiani, E., Virvou, M., Howlett, R.J., Jain, L.C., Eds.; Springer: Berlin/Heidelberg, Germany, 2010; Volume 6. [Google Scholar] [CrossRef]
- Lu, D.; Liu, T. The application of IOT in medical system. In Proceedings of the 2011 IEEE International Symposium on IT in Medicine and Education, Cuangzhou, China, 9–11 December 2011; Volume 1, pp. 272–275. [Google Scholar]
- Borovska, P.; Ivanova, D.; Kadurin, V. Experimental Framework for the Investigations in Internet of Medical Imaging Things Ecosystem. In Proceedings of the QED 17, Sofia, Bulgaria, October 2017; pp. 20–21. [Google Scholar]
- Kumar, M.A.; Sekhar, Y.R. Android based healthcare monitoring system. In Proceedings of the 2015 International Conference on Innovations in Information, Embedded and Communication Systems (ICIIECS), Coimbatore, India, 19–20 March 2015; pp. 1–5. [Google Scholar] [CrossRef]
- Getson, C.; Nejat, G. The adoption of socially assistive robots for long-term care: During COVID-19 and in a post-pandemic society. Healthc. Manag. Forum 2022, 35, 301–309. [Google Scholar] [CrossRef] [PubMed]
- Giansanti, D. The Rehabilitation and the Robotics: Are They Going Together Well? Healthcare 2021, 9, 26. [Google Scholar] [CrossRef]
- Nizamis, K.; Athanasiou, A.; Almpani, S.; Dimitrousis, C.; Astaras, A. Converging Robotic Technologies in Targeted Neural Rehabilitation: A Review of Emerging Solutions and Challenges. Sensors 2021, 21, 2084. [Google Scholar] [CrossRef]
- The da. Vinci Surgical System, the Manufacturer Website. Available online: http://www.intuitivesurgical (accessed on 13 December 2022).
- Iftikhar, M.; Majid, M.J.; Muralindran, M.; Thayabaren, G.; Vigneswaran, R.; Brendan, T.T.K. Otorob: Robot for orthopaedic surgeon roboscope: Non-interventional medical robot for tele rounding. In Proceedings of the 5th International Conference on Bioinformatics and Biomedical Engineering, Wuhan, China, 10–12 May 2011; pp. 1–5. [Google Scholar]
- Balasubramanian, S.; Klein, J.; Burdet, E. Robot-assisted rehabilitation of hand. function. Curr. Opin. Neurol. 2010, 23, 661–670. [Google Scholar] [CrossRef] [PubMed]
- Nef, T.; Mihelj, M.; Riener, R. Armin: A robot for patient-cooperative arm therapy. Med. Biol. Eng. Comput. 2007, 45, 887–900. [Google Scholar] [CrossRef]
- Kaczmarski, M.; Granosik, G. Rehabilitation robot rrh1. Arch. Mech. Eng. 2011, 58, 105–113. [Google Scholar] [CrossRef]
- Mariappan, M.; Ganesan, T.; Ramu, V.; Iftikhar, M. Intelligent Robotics and Applications, chapter Safety System and Navigation for Orthopaedic Robot (OTOROB); Springer: Berlin/Heidelberg, Germany, 2011; pp. 358–367. [Google Scholar]
- Mukai, T.; Hirano, S.; Nakashima, H.; Kato, Y.; Sakaida, Y.; Guo, S.; Hosoe, S. Development of a nursing-care assistant robot riba that can lift a human in its arms. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, Taipei, Taiwan, 18–22 October 2010. [Google Scholar]
- Kraft, K.; Smart, W.D. Seeing is comforting: Effects of tele-operator visibility in robot-mediated health care. In Proceedings of the ACM/IEEE International Conference on Human-Robot Interaction, Park, New Zealand, 7–10 March 2016; pp. 11–18. [Google Scholar]
- Giovanni, M.; Antonia, P.; Paola, M.; Daniele, G. Ethics and Automated Systems in the Health Domain: Design and Submission of a Survey on Rehabilitation and Assistance Robotics to Collect Insiders’ Opinions and Perception. Healthcare 2022, 10, 778. [Google Scholar]
- Tietze, M.; Mcbride, S. Robotics and The Impact On Nursing Practice Case Study and Pilot Site Analyses. 2020. Available online: https://www.nursingworld.org/~494055/globalassets/innovation/robotics-and-the-impact-on-nursing-practice_print_12-2-2020-pdf-1.pdf (accessed on 13 December 2022).
- Mendez, I.; Jong, M.; Keays-White, D.; Turner, G. The use of remote presence for health care delivery ina northern Inuit community: A feasibility study. Int. J. Circ. Health 2013, 72, 21112. [Google Scholar] [CrossRef]
- Oña, E.D.; Garcia-Haro, J.M.; Jardón, A.; Balaguer, C. Robotics in Health Care: Perspectives of Robot-Aided Interventions in Clinical Practice for Rehabilitation of Upper Limbs. Appl. Sci. 2019, 9, 2586. [Google Scholar] [CrossRef] [Green Version]
- Tzafestas, S.G. Ethics in Robotics and Automation: A general view. Int. Robot. Autom. J. 2018, 4, 1. [Google Scholar] [CrossRef] [Green Version]
- Agnihotri, R.; Gaur, S. Robotics: A new paradigm in geriatric healthcare. Gerontechnology 2016, 15, 146–161. [Google Scholar] [CrossRef]
- Chehri, A.; Moutah, H.T. Survivable and Scalable Wireless Solution for E-health and E-emergency Applications. In Proceedings of the EICS4Med, Pisa, Italy, 13–16 June 2011; pp. 25–29. [Google Scholar]
- Glauser, W. Blood-delivering drones saving lives in Africa and maybe soon in Canada. Can. Med. Assoc. J. 2018, 190, E88–E89. [Google Scholar] [CrossRef] [Green Version]
- Carrillo-Larco, R.M.; Moscoso-Porras, M.; Taype-Rondan, A.; Ruiz-Alejos, A.; Bernabe-Ortiz, A. The use of unmanned aerial vehicles for health purposes: A systematic review of experimental studies. Glob. Health Epidemiol. Genom. 2018, 3, e13. [Google Scholar] [CrossRef] [PubMed]
- Hampson, M. Drone delivers human kidney: The organ was flown several kilometers by a drone without incurring damage. IEEE Spectr. 2019, 56, 7–9. [Google Scholar] [CrossRef]
- Lippi, G.; Mattiuzzi, C. Biological samples transportation by drones: Ready for prime time? Ann. Transl. Med. 2016, 4, 92. Available online: http://www..ncbi.nlm.nih..gov/pubmed/27047951 (accessed on 13 December 2022). [CrossRef] [PubMed] [Green Version]
- Rosser, J.C.; Vignesh, V.; Terwilliger, B.A.; Parker, B.C. Surgical and Medical Applications of Drones: A Comprehensive Review. JSLS J. Soc. Laparoendosc. Surg. 2018, 22, e2018.00018. Available online: http://www.ncbi.nlm.nih.gov/pubmed/30356360 (accessed on 13 December 2022). [CrossRef]
- Scott, J.E.; Scott, C.H. Drone Delivery Models for Health-care. In Proceedings of the 50th Hawaii International Conference on System Sciences, Village, HI, USA, 4–7 January 2017; pp. 3297–3304. [Google Scholar]
- Thiels, C.A.; Aho, J.M.; Zietlow, S.P.; Jenkins, D.H. Use of unmanned aerial vehicles for medical. Product. Transport. Air Med. J. 2015, 34, 104–108. [Google Scholar]
- Pulver, A.; Wei, R.; Mann, C. Locating AED Enabled Medical Drones to Enhance Cardiac Arrest Response Times. Prehospital Emerg. Care 2016, 20, 378–389. [Google Scholar] [CrossRef]
- Hiebert, B.; Nouvet, E.; Jeyabalan, V.; Donelle, L. The Application of Drones in Healthcare and Health-Related Services in North America: A Scoping Review. Drones 2020, 4, 30. [Google Scholar] [CrossRef]
- Knoblauch, A.M.; de la Rosa, S.; Sherman, J.; Blauvelt, C.; Matemba, C.; Maxim, L. Bi-directional drones to strengthen health-care provision: Experiences and lessons from Madagascar, Malawi and Senegal. BMJ Glob. Health 2019, 4, e001541. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Canadian Agency for Drugs and Technology in Health. Health Technology Update: A Newsletter on New and Emerging Health Care Technologies in Canada Rural and Remote Issue. 2018. Available online: https://www.cadth.ca/sites/default/files/hs-eh/en0015-htu_issue25-final.pdf (accessed on 13 December 2022).
- Balasingam, M. Drones in medicine-The rise of the machines. Int. J. Clin. Pract. 2017, 71. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Al-Zayer, M.; Trelligus, S.; Bhandari, J.; Dave, F.S.; Folmer, E. Exploring the use of a drone to guide blindrunners. In Proceedings of the ASSETS 2016: Proceedings of the 18th International ACM SIGACCESS Conference on Computers and Accessibility, Reno, NV, USA, 23–26 October 2016; ACM: New York, NY, USA, 2016; pp. 263–264. [Google Scholar]
- Francisco, M. Organ delivery by 1000 Drones. Nat. Biotechnol. 2016, 34, 684. [Google Scholar] [CrossRef] [PubMed]
- Ling, G.; Draghic, N. Aerial drones for blood delivery. Transfusion 2019, 59, 1608–1611. [Google Scholar] [CrossRef] [Green Version]
- Al-Rawabdeh, A.; Moussa, A.; Foroutan, M.; El-Sheimy, N.; Habib, A. Time series UAV image-based pointclouds for landslide progression evaluation applications. Sensors 2017, 17, 2378. [Google Scholar] [CrossRef] [Green Version]
- Cohen, J. Natural. disasters: Drone spy plane helps fight California fires. Science 2007, 318, 727. [Google Scholar] [CrossRef]
- Dunnington, L.; Nakagawa, M. Fast and safe gas detection from underground coal fire by drone fly over Environ. Pollution 2017, 229, 139–145. [Google Scholar] [CrossRef]
- Levine, J.S.; Ambrosia, V.; Brass, J.A.; Davis, R.E.; Dull, C.W.; Greenfield, P.H.; Harrison, F.W.; Killough, B.D.; Kist, E.H.; Pinto, J.P. Monitoring wildfires using an autonomous aerial system (AAS). Remote Sens. Appl. Glob. Position. Syst. 2004, 5661, 104–120. [Google Scholar]
- Jain, T.; Sibley, A.; Stryhn, H.; Hubloue, I. Comparison of Unmanned Aerial Vehicle Technology Versus Standard Practice in Identification of Hazards at a Mass. Casualty Incident Scenario by Primary Care Paramedic Students. Disast. Med. Public Health Prep. 2018, 12, 631–634. [Google Scholar] [CrossRef]
- Jalal, A.H.; Umasankar, Y.; Christopher, F.; Pretto, E.A.; Bhansali, S. A model for safe transport of critical patients in unmanned drones with a ‘watch’ style continuous anesthesia sensor. J. Electro. chem. Soc. 2018, 165, B3071–B3077. [Google Scholar] [CrossRef] [Green Version]
- Cardil, A.; Monedero, S.; Ramírez, J.; Silva, C.A. Assessing and reinitializing wildland fire simulations through satellite active fire data. J. Environ. Manag. 2019, 231, 996–1003. [Google Scholar] [CrossRef]
- Zailani, M.A.H.; Sabudin, R.Z.A.R.; Rahman, R.A.; Saiboon, I.M.; Ismail, A.; Mahdy, Z.A. Drone for medical products transportation in maternal healthcare: A systematic review and framework for future research. Medicine 2020, 99, e21967. [Google Scholar] [CrossRef]
- Chehri, A.; Mouftah, H.T. Internet of Things—Integrated IR-UWB technology for healthcare applications. Concurr. Comput. Pract. Exper 2020, 32, e5454. [Google Scholar] [CrossRef]
- Kotlinski, M.; Calkowska, J.K. U-Space and UTM Deployment as an Opportunity for More Complex UAV Operations Including UAV Medical Transport. J. Intell. Robot Syst. 2022, 106, 12. [Google Scholar] [CrossRef] [PubMed]
- Bogle, B.; Rosamond, W.D.; Snyder, K.T.; Zègre-Hemsey, J.K. The case for drone-assisted emergency responseto cardiac arrest. North Carol. Med. J. 2019, 80, 204–212. [Google Scholar] [CrossRef] [PubMed]
- Boutilier, J.J.; Brooks, S.C.; Janmohamed, A.; Byers, A.; Buick, J.E.; Zhan, C.; Schoellig, A.P.; Cheskes, S.; Morison, L.J.; Chan, T.C. Optimizing a Drone Network to Deliver Automated External Defibrillators. Circulation 2017, 135, 2454–2465. [Google Scholar] [CrossRef]
- Zègre-Hemey, J.K.; Bogle, B.; Cunningham, C.J.; Snyder, K.; Rosamond, W. Delivery of Automated External Defibrillators (AED) by Drones: Implications for Emergency Cardiac Care. Curr. Cardiovasc. Risk Rep. 2018, 12, 3–7. [Google Scholar]
- Kim, S.J.; Lim, G.J.; Cho, J.; Côté, M.J. Drone-Aided Health-care Services for Patients with Chronic Diseases in Rural Areas. J. Intell. Robot. Syst. Theory Appl. 2017, 88, 163–180. [Google Scholar] [CrossRef]
- Amukele, T.K.; Sokoll, L.J.; Pepper, D.; Howard, D.P.; Street, J. Can unmanned aerial systems (Drones) be used for the routine transport of chemistry, hematology, and coagulation laboratory specimens. PLoS ONE 2015, 10, e0134020. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Amukele, T.K.; Streetl, J.; Carroll, K.; Miller, H.; Zhang, S.X. Drone transport of microbes in blood and sputum oratory specimens. J. Clin. Microbiol. 2016, 54, 2622–2625. [Google Scholar] [CrossRef] [PubMed]
- Scalea, J.R.; Restaino, S.; Scassero, M.; Blankenship, G.; Bartlett, S.T.; Wereley, N. An initial investigation of unmanned aircraft systems (UAS) and real-time organ status measurement for transporting human organs. IEEE J. Transl. Eng. Health Med. 2018, 6, 1–7. [Google Scholar] [CrossRef] [PubMed]
- Van Tilburg, C. First Report of Using Portable Unmanned Aircraft Systems (Drones) for Search and Rescue. Wilderness Environ. Med. 2017, 28, 116–118. [Google Scholar] [CrossRef] [Green Version]
- Clark, D.G.; Ford, J.D.; Tabish, T. What role can unmanned aerial vehicles play in emergency response in the Arctic: A case study from Canada. PLoS ONE 2018, 13, e0205299. [Google Scholar] [CrossRef] [Green Version]
- Braun, J.; Gertz, S.D.; Furer, A.; Bader, T.; Frenkel, H.; Chen, J.; Glassberg, E.; Nachman, D. The promising future of drones in prehospital medical care and its application to battlefield medicine. J. Trauma Acute Care Surg. 2019, 87 (Suppl. 1), S28–S34. [Google Scholar] [CrossRef]
- Homier, V.; de Champlain, F.; Nolan, M.; Fleet, R. Identification of Swimmers in Distress Using Unmanned Aerial Vehicles: Experience at the Mont-Tremblant IRONMAN Triathlon. Prehospital Emerg. Care 2020, 24, 451–458. [Google Scholar] [CrossRef]
- Jain, T.; Sibley, A.; Stryhn, H.; Hubloue, I. Comparison of unmanned aerial vehicle technology-assisted triage versus standard practice in triaging casualties by paramedic students in a mass-casualty incident scenario. Prehosp. Disast. Med. 2018, 33, 375–380. [Google Scholar] [CrossRef]
- Available online: https://search-proquest-com.ezproxy.library.wur.nl/wire-feeds/drone-package-delivery-market-hit-usd-7-388-2/docview/2465400967/se-2?accountid=27871 (accessed on 13 December 2022).
- Gupta, R.; Bhattacharya, P.; Tanwar, S.; Kumar, N.; Zeadally, S. Ga Ru Da: A Block chain-Based Delivery Scheme Using Drones for Healthcare 5.0 Applications. IEEE Internet Things Mag. 2021, 4, 66. [Google Scholar] [CrossRef]
- Mehta, P.L.; Kalra, R.; Prasad, R. A Backdrop Case Study of AI.-Drones in Indian Demographic Characteristics Emphasizing the Role of AI in Global Cities Digitalization, Wireless. Pers. Commun. 2021, 118, 301–321. [Google Scholar] [CrossRef]
- Ahmed, I.; Chehri, A.; Jeon, G.; Piccialli, F. Automated Pulmonary Nodule Classification and Detection Using Deep Learning Architectures. IEEE/ACM Trans. Comput. Biol. Bioinform. 2022. Available online: https://pubmed.ncbi.nlm.nih.gov/35853048/ (accessed on 13 December 2022). [CrossRef] [PubMed]
- Angurala, M.; Bala, M.; Bamber, S.S.; Kaur, R.; Singh, P. An internet of things assisted drone based approach to reduce rapid spread of COVID-19. J. Saf. Sci. Resil. 2020, 1, 31–35. [Google Scholar] [CrossRef]
- Sedig, K.; Seaton, M.; Drennan, I.; Cheskes, S.; Dainty, K. Drones Are a Great Idea! What Is an AED? Novel Insights from a Qualitative Study on Public Perception of Using Drones to Deliver Automatic External Defibrillators. Available online: www.journals.elsevier.com/resuscitation-plus (accessed on 13 December 2022).
- Uttam, P. Drones Optimized Therapy System. (DrOTS): Use of Drones for Tuberculosis Diagnosis in Nepal. Int. J. Hum. Health Sci. (IJHHS) 2019, 14. [Google Scholar] [CrossRef]
- Cawthorne, D. Aimee Robbins-van Wyns berghe., An Ethical Framework for the Design., Development, Implementation, and Assessment of Drones Used in Public Healthcare. Sci. Eng. Ethics 2020, 26, 2867–2891. [Google Scholar] [CrossRef]
- Mc Call, B. Sub-Saharan Africa leads the way in medical drones. Lancet 2019, 393, 17–18. [Google Scholar] [CrossRef] [PubMed]
- Robakowska, M.; Ślęzak, D.; Żuratyński, P.; Tyrańska-Fobke, A.; Robakowski, P.; Prędkiewicz, P.; Zorena, K. Possibilities of Using UAVs in Pre-Hospital Security for Medical Emergencies. Int. J. Environ. Res. Public Health 2022, 19, 10754. [Google Scholar] [CrossRef] [PubMed]
- Guillen-Perez, A.; Cano, M.D. Flying ad hoc networks: A new domain for network communications. Sensors 2018, 18, 3571. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Chehri, A. Energy-efficient modified DCC-MAC protocol for IoT in e-health applications. Internet Things 2021, 14, 100119. [Google Scholar] [CrossRef]
- Kaur, S. How is “internet of the 3d printed products” going to affect our lives. IETE Tech. Rev. 2012, 29, 360–364. [Google Scholar] [CrossRef]
- Ryan, T.; Hubbard, D. 3D-printing hazards: Literature review & Preliminary hazard assessment. Prof. Saf. 2016, 56–62. Available online: http://www.asse.org/assets/1/7/F1Rya_0616z.pdf (accessed on 13 December 2022).
- Mendoza, H.R. Surgeons Create 3D-printed Custom Implant to Restore Pelvis after Resection. 2015. Available online: https://3dprint.com/91580/3d-printed-pelvic-implant/ (accessed on 11 August 2016).
- Available online: http://www.notimpossible.com/ (accessed on 11 August 2016).
- Molitch Hou, M. 3D-printingEnables Medical Models with Blood. Guts, & All. 2015. Available online: http://3dprintingindustry.com/news/3d-printing-enables-medicalmodels-with-blood-guts-all-44186/ (accessed on 13 December 2022).
- Available online: http://envisiontec.com/trends-in-3d-printing-of-customized-medical-devices/ (accessed on 11 August 2016).
- Elsenpeter, R. 10 Things You Need to Know about 3D Printing. Available online: http://www.dentalproductsreport.com/dental/article/10-things-you-need-knowabout-3d-printing (accessed on 11 August 2016).
- Barnatt, C. Medical 3D-Printing. 2013. Available online: https://www.youtube.com/watch?v=P2peq82e8is (accessed on 11 August 2016).
- Hull, C. Available online: https://en.wikipedia.org/wiki/Chuck_Hull (accessed on 13 December 2022).
- 3D Systems. Available online: https://en.wikipedia.org/wiki/3D_Systems (accessed on 13 December 2022).
- Apparatus for Production of Three-Dimensional Objects by Stereo Lithography. Available online: https://www.google.com/patents/US4575330 (accessed on 13 December 2022).
- Comparison between 3D-Printing and Traditional Manufacturing Processes for Plastics. Available online: https://www.sculpteo.com/en/3d-printing/3d-printing-andtraditional-manufacturing-processes/ (accessed on 13 December 2022).
- What is 3D Printing? Available online: http://3dprinting.com/what-is-3d-printing/ (accessed on 13 December 2022).
- Grunewald, S.J. Doctors Use 3D-Printing to Safeguard an Unborn Baby’s Life. 2015. Available online: https://3dprint.com/99905/3d-printing-to-safeguard-stetfetus/ (accessed on 13 December 2022).
- Available online: http://envisiontec.com/3d-printing-industries/hearing-aid/ (accessed on 11 August 2016).
- 3D-printing Helps Develop the World’s Smallest Hearing Aid. Available online: http://www.3ders.org/articles/20130103-.3d-printing-helps-develop-the-worldsmallest-hearing-aid.html (accessed on 13 December 2022).
- Cochlear Implant Surgical Workshop-19th Window Approach Workshop in Kajetany. Available online: http://whc.ifps.org.pl/2015/01/warsztaty-szkoleniowe-z-zakresuchirurgii-implantow-slimakowych-xix-window-approach-workshop-waw-wkajetanach (accessed on 13 December 2022).
- Objet30 Ortho Desk. Available online: http://www.stratasys.com/industries/dental/objet30-orthodesk (accessed on 13 December 2022).
- Available online: http://www.zenith3d.co.kr/eng/ (accessed on 13 December 2022).
- Available online: http://envisiontec.com/3d-printing-industries/dental (accessed on 13 December 2022).
- How About Them Gams. 3D. Printing Custom Legs. Available online: http://www.businessweek.com/articles/2012-05-03/how-about-them-gams-3d-printing-custom-legs (accessed on 13 December 2022).
- Researchers Develop 3D. Printed Scaffolds to Cure Type. 1 Diabetes. Available online: http://3dprinting.com/medical/researchers-develop-3d-printed-scaffoldsto-cure-type-1-diabetes/ (accessed on 13 December 2022).
- Grunewald, S.J. Pfizer Scientists Turn to Maker Bot to Streamline Arthritis Treatment Research. Available online: https://3dprint.com/132467/pfizer-makerbot-arthritis (accessed on 13 December 2022).
- Weintraub, A. 3D. Systems Preps for Global Launch of ‘Printed.’ Knee Implants for Dogs. Available online: http://www.fiercepharma.com/animal-health/3d-systemspreps-for-global-launch-of-printed-knee-implants-for-dogs (accessed on 13 December 2022).
- Mearian. 2016. Available online: http://www.computerworld.com/article/3048823/3d-printing/this-is-the-first-3d-printed-drug-to-win-fda-approval.html (accessed on 13 December 2022).
- Longhitano, G.A.; Nunes, G.B.; Candido, G.; da Silva, J.V.L. The role of 3D printing during COVID-.19 pandemic: A review. Prog. Addit. Manuf. 2021, 6, 19–37. [Google Scholar] [CrossRef]
- Aimar, A.; Palermo, A.; Innocenti, B. Review Article the Role of 3D-printing in Medical Applications: A State of the Art Hindawi. J. Healthc. Eng. 2019, 2019, 5340616. [Google Scholar] [CrossRef] [Green Version]
- Mardis, N.J. Emerging Technology and Applications of 3D-printing in the Medical Field. Mo. Med. 2018, 115, 368–373. [Google Scholar] [PubMed]
- Shahrubudina, N.; Leea, T.; Ramlana, R. An Overview on 3D-printing Technology: Technological, Materials, and Applications, 2nd International Conference on Sustainable Materials Processing and Manufacturing (SMPM 2019). Procedia Manuf. 2019, 35, 1286–1296. [Google Scholar] [CrossRef]
- Vaish, A.; Vaish, R. 3D-printing and its applications in Orthopaedics. J. Clin. Orthop. Trauma 2018, 9S, S74–S75. [Google Scholar] [CrossRef] [PubMed]
- Dodziuk, H. Applications of 3Dprinting in healthcare. Kardiochirurgiai Torakochirurgia Pol. 2016, 13, 283–293. [Google Scholar]
- Krishna, K.D.; Akkala, V.; Bharath, R.; Rajalakshmi, P.; Mohammed, A.; Merchant, S.; Desai, U.B. Computer aided abnormality detection for kidney on FPGA based IoT enabled portable ultrasound imaging system. IRBM 2016, 37, 189–197. [Google Scholar] [CrossRef]
- Chiuchisan, I. An approach to the Verilog-based system for medical image enhancement. In Proceedings of the 2015 E-Health and Bioengineering Conference (EHB), Iasi, Romania, 19–21 November 2015; IEEE: Piscataway, NJ, USA, 2015; pp. 1–4. [Google Scholar]
- Bouhassoune, I.; Chehri, A.; Saadane, R.; Minaoui, K. Optimization of UHF RFID Five-Slotted Patch Tag Design Using PSO Algorithm for Biomedical Sensing Systems. Int. J. Environ. Res. Public Health 2020, 17, 8593. [Google Scholar] [CrossRef]
- Ahmed, I.; Jeon, G.; Chehri, A. An IoT-enabled smart health care system for screening of COVID-19 with multi layers features fusion and selection. Computing 2022. [Google Scholar] [CrossRef]
- Hassanalieragh, M.; Page, A.; Sharma, G.; Aktas, M.; Mateos, G.; Kantarci, B.; Andreescu, S. Health monitoring and management using Internet-of-Things (IoT) sensing with cloud-based processing Opportunities and challenges. In Proceedings of the 2015 IEEE International Conference on Services Computing, New York City, NY, USA, 2–27 July 2015; IEEE: Piscataway, NJ, USA, 2015; pp. 285–292. [Google Scholar]
- Tyagi, S.; Agarwal, A.; Maheshwari, P. A conceptual framework for IoT-based health-care system using cloud computing. In Proceedings of the 2016 6th International Conference-Cloud System and Big-data Engineering, Noida, India, 14–15 January 2016; IEEE: Piscataway, NJ, USA, 2016; pp. 503–507. [Google Scholar]
- Available online: https://www.resonai.com/blog/5-examples-of-augmented-reality-in-modern-health-care-facilities (accessed on 13 December 2022).
- Available online: https://www.fi.edu/difference-between-ar-vr-and-mr (accessed on 13 December 2022).
- Richard, S.C. Kerr, Surgery in the 2020.s: Implications of advancing technology for patients and the workforce. Future Healthc. J. 2020, 7, 46–49. [Google Scholar] [CrossRef] [Green Version]
- Graur, F. Virtual Reality in Medicine Going Beyond the Limits, the Thousand Faces of Virtual Reality; Intech Open: London, UK, 20 November 2014. [Google Scholar] [CrossRef] [Green Version]
- Rodday, N. Hacking a Professional Drone. 2016. Available online: www.blackhat.com/docs/asia-16/materials/asia-16-Rodday-Hacking-A-Professional-Drone.pdf (accessed on 13 December 2022).
- Yiannakopoulou, E.; Nikiteas, N.; Perrea, D.; Tsigris, C. Virtual reality simulators and training in laparoscopic surgery. Int. J Surg. 2015, 13, 60–64. [Google Scholar] [CrossRef]
- Baus, O.; Bouchard, S. Moving from virtual reality exposure-based therapy to augmented reality exposure-based therapy: A review. Front. Hum. Neurosci. 2014, 8, 112. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Merel, T. The 7 drivers of the $150 billion AR/VR Industry. Aol. Tech 2015. Available online: https://techcrunch.com/2015/07/08/the-7-drivers-of-the-150-billion-arvr-industry/ (accessed on 13 December 2022).
- Beyer-Berjot, L.; Berdah, S.; Hashimoto, D.A.; Darzi, A.; Aggarwal, R. A virtual reality training curriculum for laparoscopic colorectal surgery. J. Surg. Educ. 2016, 73, 932–941. [Google Scholar] [CrossRef] [PubMed]
- Azuma, R.T. A survey of augmented reality. Presence Tele-Oper. Virtual Environ. 1997, 6, 355–385. [Google Scholar] [CrossRef]
- Gonzalez, D.S.; Moro, A.D.; Quintero, C.; Sarmiento, W.J. Fear Levels in Virtual Environments, an Approach to Detection and Experimental User Stimuli Sensation. In Proceedings of the 2016 XXI Symposium on Signal Processing, Images and Artificial Vision (STSIVA), Bucaramanga, Colombia, 31 August–2 September 2016; pp. 1–6. [Google Scholar] [CrossRef]
- Döllinger, N.; Wienrich, C.; Wolf, E.; Botsch, M.; Latoschik, M.E. Vitras—Virtual Reality Therapy by Stimulation of Modulated Body Image -Project Outline. In Proceedings of the Mensch und Computer 2019-Workshop Band, Hamburg, Germany, 8–11 September 2019; GesellschaftfürInformatike. V.: Bonn, Germany, 2019; pp. 606–611. [Google Scholar]
- Hamzeheinejad, N.; Roth, D.; Götz, D.; Weilbach, F.; Latoschik, M.E. Physiological Effectivity and User Experience of Immersive Gait Rehabilitation. In Proceedings of the 2019 IEEE Conference on Virtual Reality and 3D User Interfaces (VR), Osaka, Japan, 23–27 March 2019; IEEE: Piscataway, NJ, USA, 2019; pp. 1421–1429. [Google Scholar] [CrossRef]
- Nebeling, M.; Madier, K. 360-proto: Making Interactive Virtual Reality & Augmented Reality Prototypes. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, Scotland, UK, 4–9 May 2019; IEEE: Piscataway, NJ, USA, 2019; pp. 1–13. [Google Scholar]
- Jackson, B.; Keefe, D.F. Lift-off: Using Reference Imagery and Freehand Sketching to Create 3d Models in Vr. IEEE Trans. Vis. Comput. Graph. 2016, 22, 1442–1451. [Google Scholar] [CrossRef]
- Aguiar Noury, G.; Walmsley, A.; Jones, R.B.; Gaudl, S.E. The Barriers of the Assistive Robotics Market—What Inhibits Health Innovation? Sensors 2021, 21, 3111. [Google Scholar] [CrossRef]
- Hussain, A.; Ali, T.; Althobiani, F.; Draz, U.; Irfan, M.; Yasin, S.; Shafiq, S.; Safdar, Z.; Glowacz, A.; Nowakowski, G.; et al. Security Framework for IoT Based Real-Time Health Applications. Electronics 2021, 10, 719. [Google Scholar] [CrossRef]
- Iqbal, N.; Imran; Ahmad, S.; Ahmad, R.; Kim, D.-H. Scheduling Mechanism Based on Optimization Using IoT-.Tasks Orchestration for Efficient Patient Health Monitoring. Sensors 2021, 21, 5430. [Google Scholar] [CrossRef] [PubMed]
- Bouhassoune, I.; Chaibi, H.; Saadane, R.; Chehri, A. Performance of On-Skin RFID Miniaturized Dual Loop Tag for Body-Centric Applications. In Human Centred Intelligent Systems. KES-HCIS 2021; Zimmermann, A., Howlett, R.J., Jain, L.C., Schmidt, R., Eds.; Smart Innovation, Systems and Technologies; Springer: Singapore, 2021; Volume 244. [Google Scholar] [CrossRef]
- Paul, A.; Pinjari, H.; Hong, W.-H.; CheolSeo, H.; Rho, S. Fog Computing-Based IoT for Health Monitoring System. Hindawi J. Sens. 2018, 2018, 1386470. [Google Scholar] [CrossRef]
- Halbig, A.; Babu, S.K.; Gatter, S.; Latoschik, M.E.; Brukamp, K.; von Mammen, S. Opportunities and Challenges of Virtual Reality in Healthcare—A Domain Experts Inquiry. Front. Virtual Real. 2022, 3, 837616. [Google Scholar] [CrossRef]
- Coelho, G.; Rabelo, N.N.; Vieira, E.; Mendes, K.; Zagatto, G.; Santos de Oliveira, R.; Raposo-Amaral, C.E.; Yoshida, M.; de Souza, M.R. Augmented reality and physical hybrid model simulation for preoperative planning of metopic craniosynostosis surgery. Neurosurg. Focus 2020, 48, E19. [Google Scholar] [CrossRef] [Green Version]
- Morimoto, T.; Kobayashi, T.; Hirata, H.; Otani, K.; Sugimoto, M.; Tsukamoto, M.; Yoshihara, T.; Ueno, M.; Mawatari, M. XR (Extended Reality: Virtual Reality, Augmented Reality, Mixed Reality) Technology in Spine Medicine Status Quo and Quo Vadis. J. Clin. Med. 2022, 11, 470. [Google Scholar] [CrossRef] [PubMed]
- Bui, D.T.; Barnett, T.; Hoang, H. Tele-mentoring using augmented reality technology in healthcare: A systematic review. Australas. J. Educ. Technol. 2021, 37. [Google Scholar] [CrossRef]
- Barsom, E.; Graafland, M.; Schijven, M.P. Systematic review on the effectiveness of augmented reality applications in medical training. Surg. Endosc. 2016, 30, 4174–4183. [Google Scholar] [CrossRef] [Green Version]
- Vidal-Balea, A.; Blanco-Novoa, Ó.; Fraga-Lamas, P.; Fernández-Caramés, T.M. Developing the Next Generation of Augmented Reality Games for Pediatric Healthcare.: An Open-Source Collaborative Framework Based on AR.Core for Implementing Teaching, Training and Monitoring Applications. Sensors 2021, 21, 1865. [Google Scholar] [CrossRef] [PubMed]
- Jain, S.; Lee, S.; Barber, S.R.; Chang, E.H.; Son, Y.-J. Virtual reality based hybrid simulation for functional endoscopic sinus surgery. IISE Trans. Healthc. Syst. Eng. 2020, 10, 127–141. [Google Scholar] [CrossRef]
- Gerup, J.; Soerensen, C.B.; Dieckmann, P. Augmented reality and mixed reality for healthcare education beyond surgery: An integrative review. Int. J. Med. Educ. 2020, 11, 1–18. [Google Scholar] [CrossRef] [Green Version]
- Bouhassoune, I.; Saadane, R.; Chehri, A. Wireless Body Area Network Based on RFID System for Healthcare Monitoring: Progress and Architectures. In Proceedings of the 2019 15th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS), Sorrento, Italy, 26–29 November 2019; pp. 416–421. [Google Scholar] [CrossRef]
- Barba, E.; Marroquin, R.Z. A primer on spatial scale and its application to mixed reality. In Proceedings of the 2017 IEEE. International Symposium on Mixed and Augmented Reality (ISMAR), Nantes, France, 9–13 October 2017. [Google Scholar] [CrossRef]
- Kersten-Oertel, M.; Jannin, P.; Collins, D.L. The state of the art of visualization in mixed reality image guided surgery. Comput. Med. Imaging Graph. 2013, 37, 98–112. [Google Scholar] [CrossRef]
- Nicolau, S.; Soler, L.; Mutter, D.; Marescaux, J. Augmented reality in laparoscopic surgical oncology. Surg. Oncol. 2011, 20, 189–201. [Google Scholar] [CrossRef]
- Meola, A.; Cutolo, F.; Carbone, M.; Cagnazzo, F.; Ferrari, M.; Ferrari, V. Augmented reality in neuro-surgery: A systematic review. Neurosurg. Rev. 2017, 40, 537–548. [Google Scholar] [CrossRef]
- Soler, L.; Ayache, N.; Nicolau, S.; Pennec, X.; Forest, C.; Delingette, H.; Mutter, D.; Marescaux, J. Virtual reality, augmented reality and robotics in surgical procedures of the liver. Perspect. Image-Guided Surg. 2004, 476. [Google Scholar]
- Soler, L.; Nicolau, S.; Schmid, J.; Koehl, C.; Marescaux, J.; Pennec, X.; Ayache, N. Virtual Reality and Augmented Reality in Digestive Surgery; IEEE Computer Society: Washington, DC, USA, 2004; pp. 278–279. [Google Scholar]
- Ahmed, I.; Chehri, A.; Jeon, G. A Sustainable Deep Learning-Based Framework for Automated Segmentation of COVID-19 Infected Regions: Using U-Net with an Attention Mechanism and Boundary Loss Function. Electronics 2022, 11, 2296. [Google Scholar] [CrossRef]
- Trevisan, D.G.; Nedel, L.P.; Macq, B.; Vanderdonckt, J. Detecting interaction variables in a mixed reality system for maxillofacial-guided surgery, 64-91501. SVR2006 2006, 39–50. [Google Scholar]
- Splechtna, R.C.; Fuhrmann, A.L.; Wegenkittl, R. Aras-augmented reality aided surgery system description, VRVis Research Center Technical Report 2002. Available online: https://www.researchgate.net/publication/228762635_Detecting_interaction_variables_in_a_mixed_reality_system_for_maxillofacial-guided_surgery (accessed on 13 December 2022).
- Salb, T.; Brief, J.; Welzel, T.; Giesler, B.; Hassefeld, S.; Muehling, J.; Dillmann, R. INPRES (intraoperative presentation of surgical planning and simulation results)–augmented reality for craniofacial surgery. Medicine 2003. [Google Scholar] [CrossRef]
- Marker, D.R.; Paweena, U.; Thainual, T.U.; Flammang, A.J.; Fichtinger, G.; Iordachita, I.; Carrino, J.; Fritz, J. 1.5T augmented reality navigated interventional MRI: Paravertebral sympathetic plexus injections. Diagn. Interv. Radiol. 2017, 23, 227. [Google Scholar] [CrossRef] [Green Version]
- Bernhardt, S.; Nicolau, S.A.; Soler, L.; Doignon, C. The status of augmented reality in laparoscopic surgery as of 2016. Med. Image Anal. 2017, 37, 66–90. [Google Scholar] [CrossRef]
- Khor, W.S.; Baker, B.; Amin, K.; Chan, A.; Patel, K.; Wong, J. Augmented and virtual reality in surgery-the digital surgical environment: Applications, limitations and legal pitfalls. Ann. Transl. Med. 2016, 4, 454. [Google Scholar] [CrossRef] [Green Version]
- Lee, S.C.; Fuerst Tateno, K.; Johnson, A.; Fotouhi, J.; Osgood, G.; Tombari, F.; Navab, N. Multi-modal imaging, model-based tracking, and mixed reality visualization for ortho-paedic surgery. Healthc. Technol. Lett. 2017, 4, 168–173. [Google Scholar] [CrossRef]
- Tepper, O.M.; Rudy, H.L.; Lefkowitz, A.; Weimer, K.A.; Marks, S.M.; Stern, C.S.; Garfein, E.S. Mixed reality with hololens: Where virtual reality meets augmented reality in the operating room. Plast. Reconstr. Surg. 2017, 140, 1066–1070. [Google Scholar] [CrossRef]
- Halic, T.; Kockara, S.; Bayrak, C.; Rowe, R. Mixed reality simulation of rasping procedure in artificial cervical disc replacement (ACDR) surgery. BMC. Bioinform. 2010, 11 (Suppl. 6), S11. [Google Scholar] [CrossRef]
- Fushima, K.; Kobayashi, M. Mixed-reality simulation for orthognathic surgery. Maxillofac. Plast. Reconstr. Surg. 2016, 38, 13. [Google Scholar] [CrossRef] [Green Version]
- Heuts, S.; Sardari Nia, P.; Maessen, J.G. Preoperative planning of thoracic surgery with use of three-dimensional reconstruction, rapid prototyping, simulation and virtual navigation. J. Vis. Surg. 2016, 2, 77. [Google Scholar] [CrossRef] [Green Version]
- Linte, C.A.; Davenport, K.P.; Cleary, K.; Peters, C.; Vosburgh, K.G.; Navab, N.; Edwards, P.E.; Jannin, P.; Peters, T.M.; Holmes, D.R., 3rd; et al. On mixed reality environments for minimally invasive therapy guidance: Systems architecture, successes and challenges in their implementation from laboratory to clinic. Comput. Med. Imaging Graph. 2013, 37, 83–97. [Google Scholar] [CrossRef] [Green Version]
- Sauer, I.M.; Queisner, M.; Tang, P.; Moosburner, S.; Hoepfner, O.; Horner, R.; Lohmann, R.; Pratschke, J. Mixed reality in visceral surgery: Development of a suitable workflow and evalu¬ation of intraoperative use-cases. Ann. Surg. 2017, 266, 706–712. [Google Scholar] [CrossRef]
- Kersten-Oertel, M.; Gerard, I.; Drouin, S.; Mok, K.; Sirhan, D.; Sinclair, D.S.; Collins, D.L. Augmented reality in neurovascular surgery: Feasibility and first uses in the operating room. Int. J. Comput. Assist Radio. Surg. 2015, 10, 1823–1836. [Google Scholar] [CrossRef]
- Hamacher, A.; Kim, S.J.; Cho, S.T.; Pardeshi, S.; Lee, S.H.; Eun, S.J.; Whangbo, T.K. Application of virtual, augmented, and mixed reality to urology. Int. Neurourolgy J. 2016, 20, 172–181. [Google Scholar] [CrossRef] [Green Version]
- Riva, G. Medical Clinical Uses of Virtual Worlds. In The Oxford Handbook of Virtuality; Grimshaw, M., Ed.; Oxford University Press: New York, NY, USA, 2014; pp. 649–665. [Google Scholar]
- Müller, S.; Maier-Hein, L.; Mehrabi, A.; Pianka, F.; Rietdorf, U.; Wolf, I.; Grenacher, L.; Richter, G.; Gutt, C.; Schmidt, J. Creation and establishment of a respiratory liver motion simulator for liver interventions. Med. Phys. 2007, 34, 4605–4608. [Google Scholar] [CrossRef]
- Ogata, T.; Onuki, J.; Takahashi, K.; Fujimoto, T. The use of computer-assisted system in ear surgery. Oto-Rhino-Laryngol. Tokyo 2005, 48, 47–51. [Google Scholar]
- Thavarajasingam, S.G.; Vardanyan, R.; Arjomandi Rad, A.; Thavarajasingam, A.; Khachikyan, A.; Mendoza, N.; Nair, R.; Vajkoczy, P. The use of augmented reality in transsphenoidal surgery: A systematic review. Br. J. Neurosurg. 2022, 36, 457–471. [Google Scholar] [CrossRef]
- Bly, R.A.; Chang, S.H.; Cudejkova, M.; Liu, J.J.; Moe, K.S. Computer-guided orbital reconstruction to improve outcomes. JAMA Facial Plast. Surg. 2013, 15, 113–120. [Google Scholar] [CrossRef] [Green Version]
- Qu, M.; Hou, Y.; Xu, Y.; Shen, C.; Zhu, M.; Xie, L.; Wang, H.; Zhang, Y.; Chai, G. Precise positioning of an intraoral distractor using augmented reality in patients with hemi facial microsomia. J. Cranio-Maxillofac. Surg. 2015, 43, 106–112. [Google Scholar] [CrossRef]
- Badiali, G.; Ferrari, V.; Cutolo, F.; Freschi, C.; Caramella, D.; Bianchi, A. Augmented reality as an aid in maxillofacial surgery: Validation of a wearable system allowing maxillary repositioning. J. Cranio-Maxillofac. Surg. 2014, 42, 1970–1976. [Google Scholar] [CrossRef] [PubMed]
- Cui, N.; Kharel, P.; Gruev, V. Augmented reality with Microsoft Holo Lens Holograms for Near Infrared Fluorescence Based. Image Guided Surgery. In Proceedings of the SPIE 2017, San Francisco, CA, USA, 8 February 2017; p. 10049. [Google Scholar]
- Pham, T.; Tang, A. User-Defined Gestures for Holographic Medical Analytics. In Proceedings of the Graphics Interface, Edmonton, Alberta, 16–19 May 2017. [Google Scholar]
- Zhang, C.; Cai, Q.; Chou, P.; Zhang, Z.; Martin-Brualla, R. Viewport: A distributed, immersive teleconferencing system with infrared dot pattern. IEEE Trans. Multimed. 2013, 20, 17–27. [Google Scholar] [CrossRef]
- Available online: https://www.wipro.com/innovation/application-of-augmented-reality-in-health-care/ (accessed on 13 December 2022).
- Available online: https://visualise.com/virtual-reality/virtual-reality-health-care (accessed on 13 December 2022).
- Goo, H.W.; Park, S.J.; Yoo, S.-J. Advanced Medical Use of Three-Dimensional Imaging in Congenital Heart Disease: Augmented Reality, Mixed Reality, Virtual Reality, and Three-Dimensional Printing. Korean J. Radiol. 2020, 21, 133–145. [Google Scholar] [CrossRef] [PubMed]
- Amini, S.; Kersten-Oertel, M. Augmented reality mastectomy surgical planning prototype using the HoloLens template for healthcare technology letters. Healthc. Technol. Lett. 2019, 6, 261–265. [Google Scholar] [CrossRef]
- Condino, S.; Turini, G.; Parchi, P.D. Open Surgery: Benefits and Limits of Mixed-Reality Using the Microsoft HoloLens. J. Healthc. Eng. 2018, 2018, 5435097. [Google Scholar] [CrossRef] [Green Version]
- Huang, C.Y.; Thomas, J.B.; Alismail, A.; Cohen, A.; Almutairi, W.; Daher, N.S.; Terry, M.H.; Tan, L.D. The use of augmented reality glasses in central line simulation: “see one, simulate many, do one competently, and teach everyone”. Adv. Med. Educ. Pract. 2018, 9, 357–363. [Google Scholar] [CrossRef] [Green Version]
- Lahanas, V.; Loukas, C.; Smailis, N.; Georgiou, E. A novel augmented reality simulator for skills assessment in minimal invasive surgery. Surg. Endosc. 2015, 29, 2224–2234. [Google Scholar] [CrossRef]
- Nomura, T.; Mamada, Y.; Nakamura, Y. Laparoscopic skill improvement after virtual reality simulator training in medical students as assessed by augmented reality simulator. Asian J. Endosc. Surg. 2015, 8, 408–412. [Google Scholar] [CrossRef]
Sl. No | Author | Ref. | Category of Health Segment | Application Type | Year |
---|---|---|---|---|---|
1 | Giovanni et al. | [19] | Robotics | Survey on rehabilitation robotics | 2022 |
2 | Tietze et al. | [20] | Barriers of assistive robotics | 2021 | |
3 | Al-Rawabdeh et al. | [21] | Robotics targeting neural rehabilitation | 2021 | |
4 | Oña et al. | [22] | Case study of robotics in nursing | 2020 | |
5 | Tzafestas et al. | [23] | Robot interventions in rehabilitation of upper limbs | 2019 | |
6 | Agnihotri et al. | [24] | Ethics involved in applicability of robotics and automation | 2018 | |
7 | Chehri et al. | [25] | Robotics in nursing | 2018 |
Drone Company | Health Items | Delivery Location |
---|---|---|
Matternet | Blood, medications | Haiti, Domnican Republic, Papua New Guinea, Switzerland |
DHL Parcel | Blood, medications | Germany |
Zipline | Vaccines, blood | Rwanda |
Flirtey | Medications | Virginia, Nevada |
Delft University | Defibrillators | Netherlands |
Sl. No | Author | Ref. | Category of Health Segment | Application Type | Year |
---|---|---|---|---|---|
1 | Gupta et al. | [64] | Drones | Medical drones in healthcare delivery | 2021 |
2 | Mehta et al. | [65] | Block chain and drone-based health delivery scheme | 2021 | |
3 | Ahmed et al. | [66] | Role of AI-drones in Indian cities’ digitalization | 2021 | |
4 | Angurala et al. | [67] | Drones in clinical microbiology and infectious diseases | 2020 | |
5 | Sedig et al. | [68] | IoT-based drones to prevent spread of COVID-19 | 2020 | |
6 | Uttam et al. | [69] | Study on public perception of drones to deliver external defibrillators | 2020 | |
7 | Hiebert et al. | [28] | Drones in healthcare services | 2020 | |
8 | Cawthorne et al. | [70] | Drones for tuberculosis diagnosis | 2020 | |
9 | Mc Call et al. | [71] | Framework for drones’ usage in healthcare | 2020 | |
10 | Robakowska et al. | [72] | Africa: Medical drones | 2019 | |
11 | Guillen-Perez et al. | [73] | Medical applications of drones | 2018 | |
12 | Chehri et al. | [74] | Flying ad hoc networks | 2018 |
Sl. No | Author | Ref | Category of Health Segment | Application Type | Year |
---|---|---|---|---|---|
1 | Longhitano et al. | [100] | 3D-printing | Review on role of 3D-printing during COVID-19 | 2021 |
2 | Aimar et al. | [101] | 3D-printing in medical applications | 2019 | |
3 | Mardis et al. | [102] | 2018 | ||
4 | Shahrubudina et al. | [103] | Overview of 3D-printing technology, materials, and applications | 2019 | |
5 | Vaish et al. | [104] | Applications of 3D-printing in orthopaedics | 2018 | |
6 | Dodziuk et al. | [105] | Applications of 3D-printing in healthcare | 2016 |
Sl. No | Author | Ref | Category of Health Segment | Application Type | Year |
---|---|---|---|---|---|
1 | Hussain et al. | [112] | IoT | IoT applications in healthcare devices | 2021 |
2 | Iqbal et al. | [113] | Security framework for IoT-based health applications | 2021 | |
3 | Bouhassoune et al. | [114] | Smart patient health monitoring system | 2021 | |
5 | Paul et al. | [115] | Remote health monitoring through wearable device and mobile application | 2019 | |
6 | Halbig et al. | [116] | Fog computing-based IoT for health monitoring system | 2018 |
Sl. No | Author | Ref. | Category of Health Segment | Application Type | Year |
---|---|---|---|---|---|
1 | Coelho et al. | [127] | VR | Challenges of VR in healthcare | 2022 |
2 | Morimoto et al. | [128] | AR | AR hybrid simulation model for preoperative planning of surgery | 2022 |
3 | Bui et al. | [129] | VR/AR/MR | VR, AR, and MR technology deployment in spine medicine | 2022 |
4 | Barsom et al. | [130] | AR | Review of AR technology in tele-mentoring for healthcare. | 2021 |
5 | Vidal-Balea et al. | [131] | An open-source framework of AR technology-based games for paediatric healthcare applications. | 2021 | |
6 | Jain et al. | [132] | VR | VR hybrid simulation model for endoscopic surgery. | 2020 |
7 | Gerup et al. | [133] | AR/MR | Review on AR and MR Technologies for healthcare education. | 2020 |
8 | Bouhassoune et al. | [134] | AR | Systematic review of AR technology in medical education. | 2020 |
9 | Goo et al. | [135] | VR/MR/AR | 3D Imaging in heart disease: AR, VR, MR and 3D-printing. | 2020 |
10 | Amini et al. | [136] | AR/HOLOENS | AR technology-based mastectomy surgical planning using HoloLens template. | 2019 |
11 | Condino et al. | [137] | MR/HOLOLENS | Pros and cons of MR-technology-based simulator for orthopaedic surgery using Microsoft Hololens | 2018 |
12 | Huang et al. | [138] | AR | Use of AR technology-based glasses in simulation. | 2018 |
13 | Lahanas et al. | [139] | A novel augmented reality simulator for skills assessment in minimal invasive surgery | 2015 | |
14 | Nomura et al. | [140] | VR and MR technologies for laparoscopic skill improvement simulator training for medical students. | 2015 |
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Siripurapu, S.; Darimireddy, N.K.; Chehri, A.; B., S.; A.V., P. Technological Advancements and Elucidation Gadgets for Healthcare Applications: An Exhaustive Methodological Review-Part-II (Robotics, Drones, 3D-Printing, Internet of Things, Virtual/Augmented and Mixed Reality). Electronics 2023, 12, 548. https://doi.org/10.3390/electronics12030548
Siripurapu S, Darimireddy NK, Chehri A, B. S, A.V. P. Technological Advancements and Elucidation Gadgets for Healthcare Applications: An Exhaustive Methodological Review-Part-II (Robotics, Drones, 3D-Printing, Internet of Things, Virtual/Augmented and Mixed Reality). Electronics. 2023; 12(3):548. https://doi.org/10.3390/electronics12030548
Chicago/Turabian StyleSiripurapu, Sridhar, Naresh K. Darimireddy, Abdellah Chehri, Sridhar B., and Paramkusam A.V. 2023. "Technological Advancements and Elucidation Gadgets for Healthcare Applications: An Exhaustive Methodological Review-Part-II (Robotics, Drones, 3D-Printing, Internet of Things, Virtual/Augmented and Mixed Reality)" Electronics 12, no. 3: 548. https://doi.org/10.3390/electronics12030548
APA StyleSiripurapu, S., Darimireddy, N. K., Chehri, A., B., S., & A.V., P. (2023). Technological Advancements and Elucidation Gadgets for Healthcare Applications: An Exhaustive Methodological Review-Part-II (Robotics, Drones, 3D-Printing, Internet of Things, Virtual/Augmented and Mixed Reality). Electronics, 12(3), 548. https://doi.org/10.3390/electronics12030548