Robotic Surgery: Precision and Automation in the Operating Room
DOI:
https://doi.org/10.55938/wlp.v1i1.99Keywords:
Robotic-Assisted Surgery, Autonomous Surgery, Minimal Invasive Surgery, Nanorobotics, Robotic Medication Delivery, Healthcare Automation, Surgical RobotsAbstract
The digitization of surgery has influenced the way doctors execute their professional responsibilities, introducing intelligence and autonomy. This change will boost surgical competency and proficiency, enabling patients to achieve the best clinical results and safety at the point of service. This chapter presents an overview of robot autonomy in commercial application and research, focusing on the problems of designing autonomous surgical robots. Modern robotic surgical systems elevate precision as well as security by leveraging innovations in materials, imaging, and visualization technologies. Acoustic feedback technologies minimize injury risk and enable remote therapy delivery, whereas tele-operation eliminates geographical barriers and allows surgeons to execute multiple types of surgeries. Computer assistance is progressively gaining momentum in emerging robot-assisted minimally invasive surgery (RAMIS) systems. Enhanced manipulating capabilities, advanced sensors, superior vision, task-level automation, proactive safety features, and data integration indicate the beginning of an era of innovation in tele-surgical robots, combined with machine learning (ML) and artificial intelligence (AI) technologies. Observing various fields, it becomes apparent that excellent quality data, obtained from efficient data gathering and communication, is a critical necessity for an effective AI which enables the establishment of real-time ML solutions.
References
D’Ettorre, C., Mariani, A., Stilli, A., y Baena, F. R., Valdastri, P., Deguet, A., ... & Stoyanov, D. (2021). Accelerating surgical robotics research: A review of 10 years with the da vinci research kit. IEEE Robotics & Automation Magazine, 28(4), 56-78.
Steil, J., Finas, D., Beck, S., Manzeschke, A., & Haux, R. (2019). Robotic systems in operating theaters: New forms of team–machine interaction in health care. Methods of information in medicine, 58(S 01), e14-e25.
Yip, M., & Das, N. (2019). Robot autonomy for surgery. In The Encyclopedia of MEDICAL ROBOTICS: Volume 1 Minimally Invasive Surgical Robotics (pp. 281-313).
Fosch-Villaronga, E., Khanna, P., Drukarch, H., & Custers, B. (2023). The role of humans in surgery automation: Exploring the influence of automation on human–robot interaction and responsibility in surgery innovation. International Journal of Social Robotics, 15(3), 563-580.
Oberlin, J., Buharin, V. E., Dehghani, H., & Kim, P. C. (2021). Intelligence and autonomy in future robotic surgery. Robotic Surgery, 183-195.
Hussain, S. M., Brunetti, A., Lucarelli, G., Memeo, R., Bevilacqua, V., & Buongiorno, D. (2022). Deep learning based image processing for robot assisted surgery: a systematic literature survey. IEEE Access, 10, 122627-122657.
Hofman, J., De Backer, P., Manghi, I., Simoens, J., De Groote, R., Van Den Bossche, H., ... & Decaestecker, K. (2024). First‐in‐human real‐time AI‐assisted instrument deocclusion during augmented reality robotic surgery. Healthcare Technology Letters, 11(2-3), 33-39.
Haidegger, T., Speidel, S., Stoyanov, D., & Satava, R. M. (2022). Robot-assisted minimally invasive surgery—Surgical robotics in the data age. Proceedings of the IEEE, 110(7), 835-846.
Brian, R., Murillo, A., Gomes, C., & Alseidi, A. (2024). Artificial intelligence and robotic surgical education. Global Surgical Education-Journal of the Association for Surgical Education, 3(1), 60.
Guntur, S. R., Gorrepati, R. R., & Dirisala, V. R. (2019). Robotics in healthcare: an internet of medical robotic things (IoMRT) perspective. In Machine learning in bio-signal analysis and diagnostic imaging (pp. 293-318). Academic Press.
Onyeogulu, T., Khan, S., Teeti, I., Islam, A., Jin, K., Rubio-Solis, A., ... & Cuzzolin, F. (2022). Situation Awareness for Automated Surgical Check-listing in AI-Assisted Operating Room. arXiv preprint arXiv:2209.05056.
Barua, R. (2024). Innovations in Minimally Invasive Surgery: The Rise of Smart Flexible Surgical Robots. In Emerging Technologies for Health Literacy and Medical Practice (pp. 110-131). IGI Global.
Nwazor, N. O., & Orakwue, S. I. (2023). Enhancing Healthcare Through Automation and Robotics. In Modernity in Health and Disease Diagnosis: The Account from STEM Women (pp. 59-67). Cham: Springer Nature Switzerland.
Kavidha, V., Gayathri, N., & Kumar, S. R. (2021). AI, IoT and robotics in the medical and healthcare field. AI and IoT‐Based Intelligent Automation in Robotics, 165-187.
Chatterjee, S., Das, S., Ganguly, K., & Mandal, D. (2024). Advancements in robotic surgery: innovations, challenges and future prospects. Journal of Robotic Surgery, 18(1), 28.
Agrawal, A., Soni, R., Gupta, D., & Dubey, G. (2024). The role of robotics in medical science: Advancements, applications, and future directions. Journal of Autonomous Intelligence, 7(3).
Gobinath, A., Rajeswari, P., Suresh, K. N., & Anandan, M. (2024). Robotics in Real-Time Applications in Healthcare Systems. In AI and IoT Technology and Applications for Smart Healthcare Systems (pp. 262-274). Auerbach Publications.
Kim, M., Choi, J., & Kim, N. (2020). Fully automated hand hygiene monitoringin operating room using 3D convolutional neural network. arXiv preprint arXiv:2003.09087.
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