Publications by authors named "Nathan J Kong"
Conditions for reliable grip force and jaw angle estimation of da Vinci surgical tools.
Int J Comput Assist Radiol Surg
January 2019
Purpose: This work presents an estimation technique as well as corresponding conditions which are necessary to produce an accurate estimate of grip force and jaw angle on a da Vinci surgical tool using back-end sensors alone.
Methods: This work utilizes an artificial neural network as the regression estimator on a dataset acquired from custom hardware on the proximal and distal ends. Through a series of experiments, we test the effect of estimation accuracy due to change in operating frequency, using the opposite jaw, and using different tools.
Article Synopsis
- Surgical robots are prone to causing tissue crush injuries during grasping due to the lack of force feedback, prompting the exploration of a blended shared control framework that incorporates real-time object identification to mitigate these risks.
- The study tests this framework on a custom robotic setup, assessing both the effectiveness of a tissue identification algorithm and the control strategy by comparing manual and blended shared control grasps on silicone tissue surrogates.
- Results show a 95% accuracy in tissue identification and a reduction in peak grasping forces with the blended control, suggesting it more effectively regulates forces during surgeries compared to traditional manual methods, and indicating a need for further research in this area.