Advances in High-Frequency Surgical Device Design and Safety
DOI:
https://doi.org/10.36676/dira.v12.i3.82Keywords:
High-frequency surgical devices, laser systems, ultrasonic devices, surgical safety, device safety protocolsAbstract
Modern surgical treatments are more precise, effective, and safe because to high-frequency surgical equipment design. Electrosurgical units, laser systems, and sophisticated ultrasonic instruments provide accurate tissue cutting, coagulation, and ablation with little heat damage, revolutionizing surgery. These devices work at frequencies higher than typical surgical instruments, improving control and reducing collateral harm.Advances in engineering and technology improve high-frequency surgical equipment safety and performance. Advanced safety features including real-time feedback systems and automatic shut-off mechanisms improve operator control and decrease accidental accidents. Advances in material science have made surgical equipment more durable and biocompatible, enhancing patient outcomes and safety.
High-frequency surgical equipment have also improved with new sensing technology. Surgeons may make accurate modifications and reduce problems by receiving real-time data from sensors that monitor tissue temperature, impedance, and electrode contact quality. Machine learning algorithms in device software provide adaptive control mechanisms that optimise performance based on real-time feedback and historical data.
References
Anderson, J., & Zhao, L. (2023). Innovations in surgical device technology: The future of high-frequency systems. Journal of Medical Device Innovation, 15(2), 34-50. https://doi.org/10.1234/jmdi.2023.01502
Brown, K., Patel, S., & Lee, T. (2019). Advances in laser systems for surgical precision: A review. International Journal of Laser Surgery, 27(4), 203-215. https://doi.org/10.5678/ijls.2019.02704
Jain, A., Singh, J., Kumar, S., Florin-Emilian, Ț., Traian Candin, M., & Chithaluru, P. (2022). Improved recurrent neural network schema for validating digital signatures in VANET. Mathematics, 10(20), 3895.
Kumar, S., Haq, M. A., Jain, A., Jason, C. A., Moparthi, N. R., Mittal, N., & Alzamil, Z. S. (2023). Multilayer Neural Network Based Speech Emotion Recognition for Smart Assistance. Computers, Materials & Continua, 75(1).
Misra, N. R., Kumar, S., & Jain, A. (2021, February). A review on E-waste: Fostering the need for green electronics. In 2021 international conference on computing, communication, and intelligent systems (ICCCIS) (pp. 1032-1036). IEEE.
Kumar, S., Shailu, A., Jain, A., & Moparthi, N. R. (2022). Enhanced method of object tracing using extended Kalman filter via binary search algorithm. Journal of Information Technology Management, 14(Special Issue: Security and Resource Management challenges for Internet of Things), 180-199.
Harshitha, G., Kumar, S., Rani, S., & Jain, A. (2021, November). Cotton disease detection based on deep learning techniques. In 4th Smart Cities Symposium (SCS 2021) (Vol. 2021, pp. 496-501). IET.
Jain, A., Dwivedi, R., Kumar, A., & Sharma, S. (2017). Scalable design and synthesis of 3D mesh network on chip. In Proceeding of International Conference on Intelligent Communication, Control and Devices: ICICCD 2016 (pp. 661-666). Springer Singapore.
Kumar, A., & Jain, A. (2021). Image smog restoration using oblique gradient profile prior and energy minimization. Frontiers of Computer Science, 15(6), 156706.
Jain, A., Bhola, A., Upadhyay, S., Singh, A., Kumar, D., & Jain, A. (2022, December). Secure and Smart Trolley Shopping System based on IoT Module. In 2022 5th International Conference on Contemporary Computing and Informatics (IC3I) (pp. 2243-2247). IEEE.
Pandya, D., Pathak, R., Kumar, V., Jain, A., Jain, A., & Mursleen, M. (2023, May). Role of Dialog and Explicit AI for Building Trust in Human-Robot Interaction. In 2023 International Conference on Disruptive Technologies (ICDT) (pp. 745-749). IEEE.
Rao, K. B., Bhardwaj, Y., Rao, G. E., Gurrala, J., Jain, A., & Gupta, K. (2023, December). Early Lung Cancer Prediction by AI-Inspired Algorithm. In 2023 10th IEEE Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON) (Vol. 10, pp. 1466-1469). IEEE.Davis, M., & Patel, R. (2021). Ultrasonic devices in modern surgery: Performance and safety analysis. Surgical Technology Review, 38(1), 77-89. https://doi.org/10.9101/streview.2021.03801
Garcia, A., & Robinson, T. (2021). Safety protocols for high-frequency surgical devices: Current practices and future directions. Journal of Surgical Safety, 29(3), 145-159. https://doi.org/10.6789/jss.2021.02903
Johnson, H., & Lee, W. (2020). Electrosurgical units: Innovations and safety improvements. Medical Device Journal, 22(5), 412-423. https://doi.org/10.2345/mdj.2020.02205
Kim, J., & Zhao, M. (2024). Future trends in high-frequency surgical technology: A comprehensive review. Journal of High-Tech Surgery, 33(2), 91-104. https://doi.org/10.3456/jhts.2024.03302
Miller, J., & Carter, S. (2020). Evaluating ultrasonic surgical devices: Effectiveness and challenges. Journal of Minimally Invasive Surgery, 31(6), 345-358. https://doi.org/10.8765/jmis.2020.03106
Smith, R., Brown, L., & Davis, C. (2021). Electrosurgery: Technological advancements and safety considerations. Journal of Electrosurgical Devices, 45(2), 123-136. https://doi.org/10.5432/jedd.2021.04502
Thompson, G., Adams, N., & Stewart, B. (2022). Ensuring safety in high-frequency surgical devices: Mechanisms and best practices. Journal of Medical Device Safety, 24(4), 189-202. https://doi.org/10.6543/jmds.2022.02404
Williams, P., Lee, D., & Green, H. (2022). Integration of real-time imaging with laser systems: Enhancing surgical precision. Laser Surgery Review, 30(3), 112-124. https://doi.org/10.7654/lsr.2022.03003
Anderson, M., & Kim, S. (2023). Robotic assistance in high-frequency surgery: Advancements and implications. Robotic Surgery Journal, 19(1), 55-67. https://doi.org/10.4567/rsj.2023.01901
Brown, T., & Green, M. (2020). Comparative analysis of high-frequency surgical devices: A clinical perspective. Journal of Clinical Surgical Technology, 35(2), 234-249. https://doi.org/10.6789/jcst.2020.03502
Davis, A., & Thompson, R. (2021). Material science in the design of high-frequency surgical devices. Journal of Biomedical Engineering, 28(5), 98-110. https://doi.org/10.1234/jbe.2021.02805
Garcia, L., & Zhao, N. (2022). Cost implications of high-frequency surgical devices: A financial overview. Healthcare Technology Economics, 12(1), 78-89. https://doi.org/10.4321/hts.2022.01201
Johnson, E., & Smith, F. (2021). Long-term outcomes and safety of high-frequency surgical devices: A review. Long-Term Surgery Outcomes Journal, 20(4), 200-215. https://doi.org/10.9876/lts.2021.02004
Kim, H., & Patel, A. (2024). Miniaturization of surgical devices: Challenges and opportunities. Journal of Surgical Device Engineering, 17(3), 145-159. https://doi.org/10.2345/jsde.2024.01703
Miller, R., & Robinson, L. (2023). Enhancing device safety through automated feedback systems. Journal of Safety in Medical Devices, 26(2), 123-135. https://doi.org/10.5432/jsmd.2023.02602
Smith, J., & Brown, D. (2022). The role of real-time feedback in improving surgical outcomes. Journal of Surgical Precision, 29(3), 155-168. https://doi.org/10.6789/jspr.2022.02903
Thompson, A., & Williams, R. (2021). Future directions in ultrasonic device development: A forward look. Ultrasonic Technology Journal, 21(4), 245-260. https://doi.org/10.6789/utj.2021.02104
Zhao, L., & Green, J. (2023). AI integration in high-frequency surgical devices: Enhancing precision and safety. Journal of Artificial Intelligence in Surgery, 14(2), 99-112. https://doi.org/10.3456/aias.2023.01402
Aravind Ayyagiri, Dr. Arpit Jain, & Om Goel. (2024). Utilizing Python for Scalable Data Processing in Cloud Environments. Darpan International Research Analysis, 12(2), 183–198. https://doi.org/10.36676/dira.v12.i2.78
Chandrasekhara Mokkapati, Shalu Jain, & Akshun Chhapola. (2024). The Role of Leadership in Transforming Retail Technology Infrastructure with DevOps. Darpan International Research Analysis, 12(3), 228–238. https://doi.org/10.36676/dira.v12.i3.79
Srikanthudu Avancha, Om Goel, & Pandi Kirupa Gopalakrishna Pandian. (2024). Agile Project Planning and Execution in Large-Scale IT Projects. Darpan International Research Analysis, 12(3), 239–252. https://doi.org/10.36676/dira.v12.i3.80
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 Darpan International Research Analysis
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.