Problem
Research questions and friction points this paper is trying to address.
gaze tracking
surgical attention
wearable eyetrackers
systematic errors
SurgGaze: Implicit Calibration for Accurate Gaze Analysis in Operating Rooms with Wearable Eyetrackers
🤖 AI Summary
为解决手术室内穿戴式眼动仪误差问题，SurgGaze利用高置信度手术时刻进行隐式校准，显著提高眼动分析精度。
📝 Abstract
Accurate gaze tracking is essential for understanding surgeons' visual attention and cognitive processes during laparoscopic surgery, yet wearable eye trackers produce large errors systematically correlated with ground-truth gaze locations, as demonstrated in Study 1. We introduce SurgGaze, an implicit calibration method that corrects these errors using high-confidence surgical moments. Building on evidence that surgeons' gaze converges near the tool-tissue contact point (TTCP) during dissection, SurgGaze uses TTCP as a surrogate for true gaze to construct training pairs. We evaluate SurgGaze in a simulated operating room trial and an authentic operating room case study. In simulation, SurgGaze reduced gaze estimation error by 40.6%, significantly outperforming conventional 9-point explicit calibration. The case study showed that these moments provide reliable training data and that calibrated gaze improves interpretation of surgeons' attention beyond numeric error reduction. These findings demonstrate that structured behavioral signals can enable implicit calibration for gaze tracking in complex real-world settings.
Innovation
Methods, ideas, or system contributions that make the work stand out.
implicit calibration
surgical moments
tool-tissue contact point (TTCP)
gaze tracking
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