4.6 Article

GRACE: Online Gesture Recognition for Autonomous Camera-Motion Enhancement in Robot-Assisted Surgery

期刊

IEEE ROBOTICS AND AUTOMATION LETTERS
卷 8, 期 12, 页码 8263-8270

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LRA.2023.3326690

关键词

AI-enabled robotics; computer architecture for robotic and automation; medical robots and systems; surgical robotics: Laparoscopy; telerobotics and teleoperation

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This article introduces an online surgical Gesture Recognition for Autonomous Camera-motion Enhancement (GRACE) system, which aims to introduce situation awareness in camera navigation during robotic-assisted surgery. Compared to current autonomous systems and clinical approaches, GRACE improves completion time and reduces workload.
Camera navigation in minimally invasive surgery changed significantly since the introduction of robotic assistance. Robotic surgeons are subjected to a cognitive workload increase due to the asynchronous control over tools and camera, which also leads to interruptions in the workflow. Camera motion automation has been addressed as a possible solution, but still lacks situation awareness. We propose an online surgical Gesture Recognition for Autonomous Camera-motion Enhancement (GRACE) system to introduce situation awareness in autonomous camera navigation. A recurrent neural network is used in combination with a tool tracking system to offer gesture-specific camera motion during a robotic-assisted suturing task. GRACE was integrated with a research version of the da Vinci surgical system and a user study (involving 10 participants) was performed to evaluate the benefits introduced by situation awareness in camera motion, both with respect to a state of the art autonomous system (S) and current clinical approach (P). Results show GRACE improving completion time by a median reduction of 18.9s (8.1% ) with respect to S and 65.1s (21.1% ) with respect to P. Also, workload reduction was confirmed by statistical difference in the NASA Task Load Index with respect to S (p < 0.05). Reduction of motion sickness, a common issue related to continuous camera motion of autonomous systems, was assessed by a post-experiment survey ( p < 0.01 ).

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