Design and validation of looping assistance methods in robotic-assisted neonatal surgical suturing in a chest model

Abstract

Background: Neonate patients have a reduced thoracic cavity, making thoracoscopic procedures even more challenging than their adult counterparts. Methods: We evaluated five control strategies for robot-assisted thoracoscopic surgical looping in simulations and experiments with a physical robotic system in a neonate surgical phantom. The strategies are composed of state-of-the-art constrained optimization and a novel looping force feedback term. Results: All control strategies allowed users to successfully perform looping. A user study in simulation showed that the proposed strategy was superior in terms of Physical demand (Formula presented.) and task duration (Formula presented.). The cumulative sum analysis of inexperienced users shows that the proposed looping force feedback can speed up the learning. Results with surgeons did not show a significant difference among control strategies. Conclusions: Assistive strategies in looping show promise and further work is needed to extend these benefits to other subtasks in robot-aided surgical suturing.