Chen Zeng Hai, Fu Hong, Lo Wai Lun, Chi Zheru, Xu Bingang
Department of Computer Science, Chu Hai College of Higher Education, Tsuen Wan, Hong Kong.
Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong.
Healthc Technol Lett. 2018 Jan 26;5(1):1-6. doi: 10.1049/htl.2016.0081. eCollection 2018 Feb.
Strabismus is one of the most common vision disorders in preschool children. It can cause amblyopia and even permanent vision loss. In addition to a vision problem, strabismus brings to both children and adults serious negative impacts in their daily life, education, employment etc. Timely diagnosis of strabismus is thus crucial. However, traditional diagnosis methods conducted by ophthalmologists rely significantly on their experiences, making the diagnosis results subjective. It is also inconvenient for those methods being used for strabismus examination in large communities such as schools. In light of that, in this Letter, the authors develop an objective, digital and automatic system based on eye-tracking technique for diagnosing strabismus. The system exploits eye-tracking technique to acquire a person's eye gaze data while he or she is looking at some targets. A group of features are proposed to characterise the gaze data. The person's strabismus condition can be diagnosed according to the features. A strabismus gaze dataset is built using the system. Experimental results on the dataset demonstrate the effectiveness of the proposed system for strabismus diagnosis.
斜视是学龄前儿童最常见的视力障碍之一。它会导致弱视甚至永久性视力丧失。除了视力问题外，斜视还给儿童和成人在日常生活、教育、就业等方面带来严重的负面影响。因此，及时诊断斜视至关重要。然而，眼科医生采用的传统诊断方法很大程度上依赖于他们的经验，使得诊断结果具有主观性。这些方法用于学校等大型社区的斜视检查也不方便。鉴于此，在这篇信函中，作者基于眼动追踪技术开发了一种客观、数字化且自动的斜视诊断系统。该系统利用眼动追踪技术在一个人注视某些目标时获取其眼睛注视数据。提出了一组特征来表征注视数据。根据这些特征可以诊断出一个人的斜视状况。使用该系统构建了一个斜视注视数据集。在该数据集上的实验结果证明了所提出的斜视诊断系统的有效性。
