Biomedical Engineering Department, Helwan University, Helwan, Egypt.
Bascom Palmer Eye Institute, University of Miami, Miami, FL, United States of America.
PLoS One. 2020 Oct 14;15(10):e0240509. doi: 10.1371/journal.pone.0240509. eCollection 2020.
To evaluate see-through Augmented Reality Digital spectacles (AR DSpecs) for improving the mobility of patients with peripheral visual field (VF) losses when tested on a walking track.
Prospective Case Series.
21 patients with peripheral VF defects in both eyes, with the physical ability to walk without assistance.
We developed the AR DSpecs as a wearable VF aid with an augmented reality platform. Image remapping algorithms produced personalized visual augmentation in real time based on the measured binocular VF with the AR DSpecs calibration mode. We tested the device on a walking track to determine if patients could more accurately identify peripheral objects.
We analyzed walking track scores (number of recognized/avoided objects) and eye tracking data (six gaze parameters) to measure changes in the kinematic and eye scanning behaviors while walking, and assessed a possible placebo effect by deactivating the AR DSpecs remapping algorithms in random trials.
Performance, judged by the object detection scores, improved with the AR DSpecs (P<0.001, Wilcoxon rank sum test) with an average improvement rate of 18.81%. Two gaze parameters improved with the activated algorithm (P<0.01, paired t-test), indicating a more directed gaze on the central path with less eye scanning. Determination of the binocular integrated VF with the DSpecs correlated with the integrated standard automated perimetry (R = 0.86, P<0.001), mean sensitivity difference 0.8 ± 2.25 dB (Bland-Altman).
AR DSpecs may improve walking maneuverability of patients with peripheral VF defects by enhancing detection of objects in a testing environment.
评估透视增强现实数字眼镜（AR DSpecs）在行走轨迹上测试时对改善周边视野（VF）缺损患者的移动能力。
前瞻性病例系列。
21 名双眼周边 VF 缺损且有行走能力的患者。
我们开发了 AR DSpecs 作为一种带有增强现实平台的可穿戴 VF 辅助设备。基于 AR DSpecs 校准模式测量的双眼 VF，图像重映射算法实时生成个性化的视觉增强。我们在行走轨迹上测试该设备，以确定患者是否能更准确地识别周边物体。
我们分析了行走轨迹得分（识别/回避物体的数量）和眼动跟踪数据（6 个注视参数），以测量行走时运动学和眼球扫描行为的变化，并通过在随机试验中停用 AR DSpecs 重映射算法来评估可能的安慰剂效应。
根据物体检测得分，使用 AR DSpecs 可提高性能（P<0.001，Wilcoxon 秩和检验），平均改善率为 18.81%。两个注视参数随着激活算法的改善而改善（P<0.01，配对 t 检验），表明中央路径的注视更有针对性，眼球扫描减少。使用 DSpecs 确定的双眼综合 VF 与综合标准自动视野计相关（R = 0.86，P<0.001），平均敏感度差异为 0.8±2.25dB（Bland-Altman）。
AR DSpecs 可通过增强测试环境中物体的检测来提高周边 VF 缺损患者的行走机动性。
