Semi-automated robotic suturing set to improve surgical outcomes
A semi-automated robotic suturing system for use in cardiac surgery is being developed to improve surgical outcomes, thanks to MIME Seed Funding.
Currently, suturing with available robotic systems is a challenging and time-consuming task that requires highly trained and skilled surgeons. The proposed system will improve the accuracy, consistency and speed of suturing, assisting surgeons reduce their workload and training costs whilst enhancing patient results.
Lead Researcher, Dr Armin Ehrampoosh, Postdoctoral Research Fellow and Principal Investigator Professor Bijan Shirinzadeh from the Department of Mechanical and Aerospace Engineering, Faculty of Engineering, at Monash University said this system will solve the limitations of existing robotic systems.
“Robotic suturing is a challenging and repetitive task that requires a high level of skill and experience, which results in long training periods and high costs for healthcare providers. The existing robotic systems currently in use have certain limitations such as complexity of controlling high degrees of freedom, lack of force feedback, and potential tissue damage. The proposed system aims to address these,” said Dr Ehrampoosh and Professor Shirinzadeh.
“The proposed system aims to reduce the workload on surgeons by developing a new needle driver mechanism that automates the suturing process, providing haptic feedback to the surgeon to assist with better sensory feedback, and offering active constraints guidance to prevent the robotic arm from entering forbidden regions, reducing the likelihood of complications during surgery. By integrating advanced methodologies like optimisation-based algorithms, machine learning, and laser-based measurements, the system will help the surgeon complete the suturing procedure with greater accuracy and consistency.”
The impact of the project will be significant for both surgeons and patients.
“For surgeons, the proposed system will reduce the burden of the suturing task, enabling them to focus on other aspects of the surgical procedure. While for patients, the system aims to improve the quality and consistency of suturing, leading to improved surgical outcomes and post-operative recovery rates. Additionally, the project has the potential to improve training for surgeons, reducing training costs and time, and potentially making cardiac surgery more accessible,” said Dr Ehrampoosh and Professor Shirinzadeh.
The project is currently in the research and development phase and has already achieved several milestones, including the development of a proof-of-concept prototype for the semi-automated needle driver mechanism, providing haptic feedback based on machine learning, and the implementation of the active constraints guidance system using virtual fixture algorithms. These developments have been validated through experiments, and research papers have been published.
Next steps include increasing robotic end-effector dexterity, enhancing the robot's autonomy through laser-based measurements that enable the robot to perform the task autonomously using the user's selected suturing points and improving the stability of virtual fixture algorithms.
Watch this space for further developments.
Acknowledgements
The team acknowledges the funding support provided by the Monash Institute of Medical Engineering (MIME). The engineering research team of Dr Armin Ehrampoosh (Postdoctoral Research Fellow -Project/Lead Researcher) and Professor Bijan Shirinzadeh (Principal Investigator) would also like acknowledge the support of their clinical partner, Professor Julian Smith (Department of Surgery) in developing the proposed system.