21 October 2021
You might have visited doctors and have heard of robotic surgeries. The process of enhancing the performance of these robotic surgical arms is lengthy, and requires collaboration among researchers, engineers, and surgeons, to generate ideas for improving these surgical robotic tools. In its development of surgical robots, R&D engineer Shashank Pasupuleti has been working alongside teams to design, build, and implement robotic arms that are used as instruments in operating rooms and explore the potential and effectiveness of minimally invasive surgery.
One of the crucial elements of ensuring the performance of such a device is verification which applies at every stage of a product’s lifecycle. This involves not only testing the physical functionality of the arms but also assessing their precision, reliability, and safety in real-world scenarios. Given the complexity of robotic surgery, a multidisciplinary approach to verification is essential, involving collaboration across various teams, from software development to mechanical design.
Testing and Troubleshooting Robotic Arms
Reflecting on his experiences, he tells us that over the years, he has been involved in optimizing several robotic arms, particularly addressing challenges such as vibration, alignment, or accuracy. The testing methods developed by him played a crucial role in ensuring the robotic arms performed as intended under the conditions they were meant to be employed in surgery. For instance, one of the major problems they solved was the vibration control problems arising from manufacturing, which could have interfered with the required accuracy in surgery. By investigating the problem and conducting multiple tests, they identified the root cause. This required ongoing collaboration with both the systems engineering and software development teams to monitor updates pushed through platforms GitLab. The results of this careful thinking, achieved a reduction in error margin by over 20%, leading to more precise and reliable surgical operations.
One of the other areas of interest was the positioning of the robotic arms, where high levels of accuracy is critical for successful surgery. Small deviations, for instance, in the millimeter range, could significantly impact the outcome of an operation. His activities also included developing test cases and fixtures for assess arm positioning in real-life scenarios, as well as addressing issues that emerged in the field with the manufacturers. This model proved essential in identifying the areas of vulnerability and optimizing the design to maintain accuracy over time.
One notable example of his work was the development of an arm absolute accuracy fixture, designed to test robotic arms’ accuracy. This fixture enabled them to quantify the actual positioning accuracy of the arms more effectively and offered valuable feedback to enhance the performance of the arm. Such testing is essential not only for testing the effectiveness of the product but also for establishing credibility among the clinical teams that will depend on these tools in the operating room.
But all these tests didn’t come with a time tag, the test cases and methods he and his team developed for robotic arms helped reduce the testing time by 15-20% across multiple test cycles. This improvement facilitated faster product development and quicker integration of feedback into the design process.
Collaboration and Cross-Functional Teamwork
Probably the most fulfilling part of his job was the ability to work with other teams such as the software, hardware, clinical, and occasionally the surgical teams. It is not just the functionality of robotic surgical arms that determines the effectiveness of robotic surgery systems but also by how seamlessly these arms integrate into the broader system. For example, he integrated himself with the clinical and navigation teams in cadaver labs to analyze practical challenges and assess the feasibility of the system in high-pressure situations. These sessions got them valuable feedback which was then incorporated into subsequent rounds of testing, resulting in design improvements.
Another key component of the verification process was the development of an Automated System for calibration, designed to ensure that the robotic arms could self-adjust and maintain their precision over time. As the leader of the V&V activities of the Calibration System, he focused on creating effective testing approaches to confirm that the system was operating as intended and could be implemented in manufacturing. The calibration system was tested and validated to maintain robotic arm accuracy with a 99.9% retention rate of their original calibration. This system played a crucial role in enhancing the long-term efficiency and reliability of the robotic arms.
Data Analysis for Improvement
In the world of robotic surgery, real-time data analysis is important. They utilized platforms like Qubole to analyze case data and extract actionable insights. Identifying recurring patterns and common issues that field instructors were facing were reported and the areas of enhancement or problems that needed to be solved were highlighted. This added an extra layer of verification to their systems, particularly for issues that are not easily identifiable during the development and testing phases of the system. Continuous improvement is a vital part of any successful product lifecycle, and in robotic surgery is no exception. The efficiency of a robotic arm in the operation room is not a fixed parameter – it grows with time, with trials, with modifications and with tests. The testing methodologies that were used in creating the tests, the development of the fixtures and the analysis of the data they collected all fed back into the design process to ensure constant updates to the designs. According to Pasupuleti, “One of the most exciting aspects of working in this field is that everything we do will have a lasting impact on the future of healthcare.”
Insights on the Future of Robotic Surgery
Looking at the current patterns, he believes that the future of robotic surgery lies in the deeper integration of advanced technologies, such as AI and machine learning to further enhance the performance and adaptability of robotic arms. While the precision and capabilities of robotic arms have already revolutionized many aspects of surgery, there is still significant room for improvement. He envisions a future where robotic systems become more intuitive, more adaptable to individual patient’s needs, and more seamlessly integrated into clinical environments.
Furthermore, the role of data will continue to expand. The ability to collect more data on robotic systems in the field will result in gaining deeper insights into how these systems perform across diverse environments and conditions. With advanced analytics, robotic surgery systems could become more predictive, anticipating potential issues before they arise and allowing for preemptive adjustments to improve patient outcomes.
Robotic systems are likely to become more widespread across a variety of minimally invasive surgical specialities beyond urology and bronchoscopy, with future innovations focusing on smaller, more flexible robotic arms. The potential is vast, but for effective functioning it requires collaboration between various teams, sharing of ideas and constant testing.