ABSTRACT In this paper, a unique approach is proposed to determine eye strain in children caused due to the prolonged exposure to LCD and PDP screens. Blink rate and area of eye sclera are the two efficient metrics relied upon to determine eye strain. Initially, blink rate is computed by monitoring state transitions from open to closed eyes. To segment the sclera region of the eye Otsu’s thresholding and colour tracking, were implemented. These approaches had limitations due to illumination and skin tone. To overcome this, Modified Otsu using Colour Tracking is proposed in this paper. The occurrence of eye strain is determined by comparing the values of the metrics derived in real time with a threshold. The proposed algorithm detects eye strain with an accuracy of 83%. After detection of fatigue an alert message is sent to caretakers.

中文翻译：

---

使用 raspberry-pi 通过眨眼率和巩膜面积检测眼睛疲劳

摘要 在本文中，提出了一种独特的方法来确定儿童因长时间接触 LCD 和 PDP 屏幕而引起的眼睛疲劳。眨眼率和眼巩膜面积是确定眼睛疲劳所依赖的两个有效指标。最初，眨眼率是通过监测从睁眼到闭眼的状态转换来计算的。为了分割眼睛的巩膜区域，实施了 Otsu 的阈值处理和颜色跟踪。由于光照和肤色，这些方法具有局限性。为了克服这个问题，本文提出了使用颜色跟踪的 Modified Otsu。眼睛疲劳的发生是通过将实时导出的度量值与阈值进行比较来确定的。所提出的算法检测眼睛疲劳的准确率为 83%。检测到疲劳后，会向看护人发送警报消息。