Scene Graph-Driven Haptic Feedback for Safety Enhancement in Robotic Ophthalmic Surgery via Physically Simulated iOCT

• URL: http://arxiv.org/abs/2609.07857v1
• Date: Mon, 07 Sep 2026 18:16:37 GMT
• Title: Scene Graph-Driven Haptic Feedback for Safety Enhancement in Robotic Ophthalmic Surgery via Physically Simulated iOCT
• Abstract summary: This paper presents a novel haptic feedback system for subretinal injection tasks leveraging Scene Graphs (SG)<n>The SG serves as a semantic abstraction layer for the surgical scene, which is then utilized by a deterministic, rule-based engine to generate state-dependent haptic feedback on a robotic input device.<n>Results demonstrate that the SG-driven haptic feedback improved surgical precision, reducing needle alignment error by 14% and improving System Usability Scale (SUS) scores by 8%.
• Score: 2.7913039067663195
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Robotic ophthalmic surgery offers high precision but introduces a "sensory gap" by decoupling the surgeon from their instrument, resulting in a loss of tactile feedback. This paper presents a novel haptic feedback system for subretinal injection tasks leveraging Scene Graphs (SG). The system bridges the sensory gap by analyzing a physically simulated intraoperative Optical Coherence Tomography (iOCT) feed to construct a real-time surgical SG. The SG serves as a semantic abstraction layer for the surgical scene, which is then utilized by a deterministic, rule-based engine to generate state-dependent haptic feedback on a robotic input device. The system was evaluated in a user study (N=16) using an anthropomorphic head phantom and a custom-built surgical robot. Results demonstrate that the SG-driven haptic feedback improved surgical precision, reducing needle alignment error by 14% (p = 0.044) and improving System Usability Scale (SUS) scores by 8% (p = 0.015), while maintaining comparable task completion times. A needle trajectory analysis revealed the emergence of a safer "Align-then-Approach" strategy, in which our haptic negative reinforcement prompted users to fine-tune the tool's trajectory before approaching the retinal target. This work suggests that SGs can effectively serve as the direct computational foundation for real-time, safety-enhancing context-aware haptic feedback in robotic microsurgery.

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