|Alternative Title||Exploring the Safety of Street-crossing and Its Effect Pattern for Glaucoma Pedestrians|
|Thesis Advisor||吴昌旭 ; 张警吁|
|Place of Conferral||北京|
|Keyword||青光眼 外周视野缺损 行人 安全边缘系数|
研究一采用比以往研究更具生态效度的过街行为实验方法，利用安全边缘系数这一行为指标来考察青光眼的过街安全性。结果发现，青光眼患者的边缘系数和正常人没有显著差异；青光眼患者做过街决策时的等待时间和错过的可通过间隔数大于正常人(t46 = -2.50，p < 0.05；t37 = -2.59，p < 0.05)，从结果可以推断，在真实的过街场景中，青光眼患者有意识地做出了安全补偿，采取了比正常人保守的过街策略，但这种安全补偿并没有明显地提高青光眼患者的过街安全性，青光眼患者面临和正常人相同的潜在危险。
研究二考察青光眼患者的车速估计能力，采用估计车速值和实际车速值之间的相关来表示被试对车速变化的敏感度，结果表明车速变化敏感度和右眼的对比敏感度有显著的正相关 (r = 0.30, p < 0.05)，也就是说，对比敏感度越好，对车速的变化越敏感；车速变化敏感度和边缘系数之间存在显著正相关 (r = 0.30, p < 0.05)，被试对车速的变化越敏感，边缘系数越大。
研究三旨在测量青光眼患者的视野缺损在空间上的表现——对来车的最大探测距离。结果显示，青光眼患者的最大探测距离显著小于正常人 (左测距：t53 = -6.03, p < 0.01；右测距：t53 = -4.46, p < 0.01；自由测距t53 = -4.46, p = 0.05)，并且随着青光眼严重度的增大的，最大探测距离逐渐减小。对于重度青光眼患者来说，在过街时，如果没有头动补偿，只有出现在其左右两侧约15 米以内的车辆才能够被其察觉到，大大增加了过街的风险。
研究四基于理论假设和前三个实验研究的结果，将视野、对比敏感度、最大探测距离合成为两个综合描述被试视觉能力的因子——左视能、右视能，对可能影响过街安全性的因素进行分层回归分析，建立了青光眼患者过街安全模式。影响模式中包含有左视能、右视能、错过的可通过车流间隔、车速估计能 力、安全边缘系数等5 个变量，结果显示左视能显著预测被试错过的可通过间隔，同时调节可通过间距对安全边缘系数的影响；右视能显著预测被试的车速估计能力，同时调节车速估计能力对安全边缘系数的影响。
|Other Abstract|| Glaucoma will lead to irreversible peripheral field loss and contrast sensitivity damage. Most of the glaucoma patients have reported traveling and street-crossing difficulty. However, few studies focused on the street-crossing safety of the glaucoma in the traffic safety region. Hence, in this study, glaucoma patients was chosen to explore the street-crossing safety of this group. Study 1 was conducted to investigate the street-crossing safety first, and then study 2 and 3 were carried out to explore what factors affect the glaucoma’s crossing safety. Based on the theoretical hypothesis and experiment results of study 1 to study 3, study 4 built an effect pattern of crossing safety.|
In study 1, a more ecological experiment design was carried out to measure the safety margin, which was an appropriate behavior indicator for street-crossing safety. The results showed no significant difference between glaucoma patients and normal people. While making crossing decision, the waiting time and missed-crossable gaps of glaucoma patients were significant larger than the normal people (t46 = -2.50，p = 0.02 < 0.05；t37 = -2.59，p = 0.013 < 0.05). Conclusion: In the real crossing task, glaucoma patients were more conservative and careful than the normal people to compensate their defective vision. However, the compensation didn’t significantly improve the crossing safety. The glaucoma patients faced the same potential risk as the normal people faced.
Study 2 was carried out to investigate the speed estimating ability. The correlation between the actual vehicle speed and the estimated vehicle speed was used to measure the sensitivity to speed change of the subjects. The result showed significant positive correlation between the sensitivity to speed change and the contrast sensitivity of the right eye (r = 0.30, p = 0.04 < 0.05) and the safety margin (r = 0.30, p = 0.03 < 0.05). Conclusion: the better the contrast sensitivity of the right eye may lead to more sensitively to the speed change. Subjects who were more sensitively to speed change may get larger safety margin.
Study 3 was conducted to measure the largest detecting distance of coming vehicle, which reveal the spatial distance of the peripheral field loss. The result showed the glaucoma patients had much smaller detecting distance than the normal people (the left detecting distance：t53 = -6.03, p < 0.01；the right detecting distance：t53 = -4.46, p < 0.01；the free detecting distance t53 = -4.46, p = 0.05). Conclusion: with the increase of the severity of the glaucoma, the largest detecting distance decreased. For the severest glaucoma patients, it is very dangerous because only vehicles within 15meters can be detected if without frequent head movement.
Based on the theoretical hypothesis and the experiment results of study 1 to 3, study 4 conducted a hierarchical regression to analyze the effect of key factors (missed crossable gap, speed estimating ability) on safety margin. Two new factors, combined by visual field, contrast sensitivity and detecting distance were introduce to measure the vision skills of the subjects. Finally, an effect pattern was built to explain the effects between left vision skills, right vision skills, missed-crossable gaps, speed estimating ability and safety margin. Results: the missed-crossable gaps can be predicted by the left vision skills, and the left skills moderated the effect of missed-crossable gaps on safety margin; the speed estimating ability can be predicted by the right vision skills, and the right vision skills moderated the effect of speed estimating ability on safety margin.
|孙柔贤. 青光眼患者的过街安全性及其影响模式探究[D]. 北京. 中国科学院研究生院,2016.|
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