Saving the warrior with semiautonomous robotic telesurgery

Steven Hong shong123@stanford.edu
Ryan Orosco orosco@stanford.edu

Abstract

Introduction: With increasing global presence and a greater expeditionary emphasis, the armed forces are in need of increasing capabilities with decreased personnel footprints.  The ability to remotely control surgical robots allows access to a wide-range of surgical expertise otherwise limited by on-site availability of care. Surgical robotic arms in field hospitals or ambulances controlled by surgeons sitting at distant and safer sites could begin to manage patients from the point of injury instead of delaying this intervention.  A study evaluating coalition combat casualties in Iraq and Afghanistan, approximately 90% of mortalities occurred prior to arrival at a medical treatment facility, with approximately 25% of those fatalities deemed survivable with quicker medical intervention.  The ‘Golden Hour’ critical time window after a serious injury could be dramatically reduced with early robotic surgical intervention. The consequences of these changes would redefine combat casualty care.  Similarly, telesurgical robots could be deployed during peacetime humanitarian missions or used in rural/remote civilian medical facilities to provide the expertise of multiple surgical specialties in one machine. Methods: Using microsurgery as a platform to test the feasibility of telerobotic surgery between extensive geographic distances, we used polyurethane micro-vessels to perform anastomoses using a modified da Vinci robot with microsurgical arms.  After internal interrogation of the network capabilities of the robot, we performed similar tasks with built-in signal latencies of different lengths as a surrogate for geographic distances and bandwidth limits. Results:   Performing anastomoses on the polyurethane vessels, without any built-in signal latencies our efficiency scores showed a baseline increase in performance as expected throughout the trial.  With increasing levels of signal latencies built-into the robot, the efficiency scores and time to completion showed a decrease in performance and increased mistakes of oscillation and over-correction as anticipated.   Conclusion: Since the mid-2000’s, telerobotic surgery has been technically possible but practically infeasible due to limited network bandwidths and excessive signal latency (time delay).  Today, despite advances in network communications, the limitation of signal latency remains a major impediment to the implementation of telerobotic surgery.  As robotic telesurgery is reinvestigated due to its immense potential for military and aerospace medicine, alternative strategies must be developed to counter-measure and mitigate excessive signal latency during robotic telesurgery.  The next phase of our project will utilize machine learning to develop and implement semi-autonomous robotic surgery protocols to improve the performance and safety of complex robotic surgical tasks in the setting of signal latency and signal disruption.    
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