目的：探索一种无创的、智能可穿戴设备监测学龄儿童量化的用眼行为，并定量分析近视发生的相关因素。方法：招募佛山市禅城区石湾第二小学三年级及狮城中学小学部五年级的年龄为7~11岁部分学生共171例。所有受试者均按照非睫状肌麻痹主觉验光结果分为近视组108例和非近视组63例，所有受试者均佩戴智能可穿戴设备“云夹”，进行为期10 d(2022年9月21日—2022年10月2日)的用眼行为数据(近距离用眼距离、近距离用眼时间、近距离环境光照、有效户外时间)采集。采用t检验比较近视组与非近视组儿童在用眼行为数据之间的差异，并应用Logistic回归分析用眼行为与近视发生的相关性。绘制受试者操作特征(receiver operating characteristic curve,ROC)曲线，并计算曲线下面积(area undercurve,AUC)分析用眼行为习惯对近视发生的预测价值。结果：学龄期儿童近视患病率为63.2%。近视组与非近视组在每天用眼时间、单次用眼时间、用眼距离、白天用眼光照、晚上用眼光照、每天户外活动时间及每天有效户外活动暴露次数比较差异均有统计学意义(均P＜0.05)。Logistic回归分析显示，单次用眼时间、每天用眼时间是近视发生的危险因素。Spearman相关性分析显示，单次用眼时间及每天用眼时间均与近视发生呈正相关(均P＜0.05)。单次用眼时间预测近视发生的ROC曲线下面积为0.939。结论：可穿戴设备“云夹”可量化学龄期儿童用眼行为；学龄期儿童近视发生可能与近距离用眼时间有一定相关性；预测模型可结合儿童屈光发育档案，量化近视发生风险，对儿童实现分类管理，及时采取个性化干预。

Objective: To investigate a non-invasive,smart device capable of monitoring the quantitative visual behavior of school age children, and to analyze quantitatively the relationship between visual behavior and the occurrence of myopia. Methods: This study recruited 171 subjects aged between 7 and 11 years from the third grade of Shiwan SecondPrimary School and the fifth grade of Shicheng Middle School in Chancheng District, Foshan City. Participants werecategorized into a myopia group (108 subjects) and a non-myopia group (63 subjects) based on results from non-ciliary muscle paralysis optometry. All subjects wore "clips" to track their near-work distance, near-work duration, lighting conditions during near-work, and time spent on outdoor activities between September 21, 2020, and October 10, 2020. Differences in these habits between the myopia and non-myopia groups were compared, and logistic regression analysis was conducted to assess the impact of habitual eye use on myopia. Results: The prevalence of myopia was found to be 63.2%. Statistically significant differences (all P<0.05) were observed between the myopic and non-myopic groups regarding average daily near-work time, average single near-work session duration, average near-work distance, average daytime and nighttime near-work lighting conditions, average daily outdoor activity time, and average daily effective outdoor activity exposure. Logistic regression analysis indicated that longer average single near-work sessions and increased average daily near-work time were risk factors for myopia. Spearman correlation analysis further supported these findings, showing a positive correlation between average single near-work session duration and average daily  near-work time with the occurrence of myopia (all P<0.05). The predictive accuracy of a model combining average single near-work session duration and average daily near-work time for myopia occurrence was high, with an area under the curve of 0.939. Conclusions: The wearable device "Cloud clip" effectively monitors the visual behavior of school-age children. The occurrence of myopia in this age group may be associated with increased near-work activities. A predictive model incorporating refractive development in myopic children can assess the quantitative risk of myopia, enabling the classification and management of school-age children. Personalized interventions may serve as protective factors against myopia.

目的：分析人眼的睑板腺形态学特征，探索睑板腺分析系统在眼表疾病的应用研究。方法：中山眼科中心入组正常受试者24例(42眼)，进行睑板腺红外摄影。选取受试者中的10例(20眼)在同型号的设备上由二名操作员分别进行睑板腺红外摄影。图像通过自行设计的分析软件对上睑结膜中央5条腺体形态学参数进行定量分析，对数据进行重复性测试。结果：测量的生物参数腺体直径为(0.48±0.09) mm，腺体长度为(5.25±0.68) mm，腺体面积为(2.12±0.53) mm，腺体形变系数为10.01±3.85，显影值为6.32±1.23，中央五条腺体占中央区域面积百分比为(10.94±2.20)%，腺体占上睑结膜面积百分比为(58.07±8.13)%。各指标两次测量值差异无统计学意义(P>0.05)。重复性分析结果显示：腺体各项生物参数的变异系数(coefficients of variation，CV)均小于5%，组内变异系数(intraclass correlation coefficient，ICC)均大于0.95。结论：睑板腺综合分析系统对腺体的形态学分析有良好的可靠性和一致性，有望为临床上对睑板腺腺体功能评估提供新的非侵入性参考指标。

Objective: To analyze the morphological characteristics of meibomian glands in human eyes and to explore the application research of meibomian glands analysis system in ocular surface diseases. Methods: A total of 24 healthy subjects were recruited by Zhongshan Ophthalmic Center to infrared photography of meibomian glands. Ten of healthy subjects were selected by the two operators for infrared photography of meibomian glands on the same model of equipment. The images were repeatedly measured and analyzed by the self-designed analysis software on the morphological measurements of the five glands in the center of the upper eyelid. Results: The measured biological parameters are shown below: the average gland diameter was (0.48±0.09) mm, the average gland length was (5.25±0.68) mm, the average gland area was (2.12±0.53) mm, the gland deformation coefficient was 10.01±3.85, the development value was 6.32±1.23, the percentage of the five central glands in the central area was (10.94±2.20)%, and the glands accounted for (58.07±8.13)% of the upper conjunctiva area. There was no statistical difference between the two measurements of each index (P>0.05). Repeatability analysis results showed that coefficients of variation (CV) of all biological parameters of glands were less than 5% and the intraclass correlation coefficient (ICC) in both groups were greater than 0.95. Conclusion: The Meibomian Gland Bioimage Analyzer provides good reliability and consistency for morphological measurements of the meibomian gland, and it is expected to provide new non-invasive indicators for clinical assessment of the meibomian glands function.