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Networked Medical Systems (NMS) promise better data exchange in medical infrastructures such as operating rooms in hospitals and clinics. However, the heterogeneous interfaces of medical systems and varied requirements on NMS such as real-time constraints, increase the communication complexity considering network architectures, communication protocols and software/hardware components. In this paper,...
BackgroundTransferring non‐trivial human manipulation skills to robot systems is a challenging task. There have been a number of attempts to design research systems for skill transfer, but the level of the complexity of the actual skills transferable to the robot was rather limited, and delicate operations requiring a high dexterity and long action sequences with many sub‐operations were impossible...
Despite the fact that minimally invasive robotic surgery provides many advantages for patients, such as reduced tissue trauma and shorter hospitalization, complex tasks (e.g. tissue piercing or knot-tying) are still time-consuming, error-prone and lead to quicker fatigue of the surgeon. Automating these recurrent tasks could greatly reduce total surgery time for patients and disburden the surgeon...
Despite the fact that minimally invasive robotic surgery provides many advantages for patients, complex tasks are still time-consuming, error-prone and lead to quicker fatigue of the surgeon. Automating recurrent tasks could greatly reduce total surgery time for patients. While surgeons gain most of the information which is necessary to perform the operation from the visual feedback of cameras, there...
Tying suture knots is a time-consuming task performed frequently during minimally invasive surgery (MIS). Automating this task could greatly reduce total surgery time for patients. Current solutions to this problem replay manually programmed trajectories, but a more general and robust approach is to use supervised machine learning to smooth surgeon-given training trajectories and generalize from them...
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