发表机构
Istanbul Medipol University（伊斯坦布尔梅迪波尔大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究评估了低成本眼动追踪系统在视力筛查中的数据采集稳定性，使用GC308和网络摄像头，以注视向量角度变化作为诊断指标。
AI 中文摘要
这项工程研究评估了在视力筛查过程中，通过使用网络摄像头和带有Orlosky眼动追踪管线的GC308近红外相机实现Gaze Quest，进行注视辅助数据采集的情况。十名受试者在两种采集条件下进行了测试。Tumbling E方向的准确性、报告的应用logMAR值和响应延迟均通过键盘响应确定，因此这些是行为输出，而非眼动追踪器的筛查结果。连续归一化注视向量之间角度的帧间变化（28.2度）作为GC308眼动追踪器衍生的诊断指标，有效采样率约为8 FPS。在当前分析中，未对GC308眼动追踪器输出数据进行屏幕目标校准或注视到屏幕的转换，因此这些数据代表采集稳定性，而非与目标相关的注视准确性。网络摄像头管线依赖于25点屏幕校准。由于显示分辨率和像素间距无法保留在研究记录中，报告的应用logMAR值在任何情况下都不能被视为视力敏锐度的度量。
英文摘要
This engineering study assesses gaze-assisted data acquisition during visual screening with a Gaze Quest implementation via webcam and GC308 near infrared camera with an Orlosky eye tracking pipeline. Ten subjects performed under both acquisition conditions. Accuracy of Tumbling E orientation, reported application logMAR value,and response latency were determined from keyboard responses and hence are behavioral outputs as opposed toeye tracker screening results. Frame-to-frame change in theangle between successive normalized gaze vectors (28.2degrees) served as the GC308 eye tracker derived diagnostic with an effective sampling rate of roughly 8 FPS. No screen target calibration or gaze to screen translation was done on the GC308 eye tracker output data for the current analysis and hence, these data represent acquisition stability and not gaze accuracy in relation to the target. The webcam pipeline relied on 25-point screen calibration. Because the display resolution and pixel pitch could not be retained in the records of the study, the reported application logMAR values cannot be viewed as measures of visual acuity in any way.
Comments5 pages, 7 figures
