シーングラフ駆動の触覚フィードバックによるロボット眼科手術の安全性向上：物理シミュレーションi OCTを用いて
Scene Graph-Driven Haptic Feedback for Safety Enhancement in Robotic Ophthalmic Surgery via Physically Simulated iOCT
ロボット眼科手術において、物理シミュレーションされたiOCT映像からシーングラフを構築し、その意味情報に基づいて触覚フィードバックを生成するシステムを提案。ユーザー実験で針の位置合わせ誤差を14%削減し、安全性を高める操作戦略の誘導を確認した。
著者: Danial Arbabi, Korab Hoxha, Angelo Henriques, Mirza Imamovic, M. Ali Nasseri
分類: cs.RO, cs.CV
原文アブストラクト
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.