智能护目镜:一种确定DES(数字眼疲劳)的设备

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引用次数: 0

摘要

目的:本发明在当前场景中非常有用,在使用数字设备超过允许时间的人群中,数字眼疲劳(DES)是一种常见的不良现象。本发明的目的是定期或在早期阶段确定DES,以便采取所需的补救措施或进行逆转以挽救我们的眼睛。背景:该设备基于一个系统,该系统将检测由于持续使用数字设备而导致的眼睛疲劳症状,如可追踪的(眨眼频率、眼睛发红、眼睛挤压和眼睛瘙痒)和不可追踪的(眼睛疼痛、流泪、视力模糊、头痛)症状,并在出现这些症状时产生警报。该系统现在安装在一个设备中以识别应变。该设备被称为“智能眼镜”。方法:系统通过不同的步骤执行。首先,系统通过摄像头采集视频并存储在模块中。视频将被分成几帧。系统将检查帧中是否存在可追踪的因素(眨眼率、发红、挤压和瘙痒)。如果其中一个可追溯因素存在,那么系统将检查另一个输入,通过输入从用户那里获得不可追溯的因素(眼痛、流泪、视力模糊和头痛)。然后将这两个输入都传递给机器学习算法(贝叶斯分类)来预测眼睛疲劳。如果分类器预测到眼睛疲劳,那么就会在用户的机器上发送警报,提醒用户眼睛疲劳状态。应用:使用数字设备来执行他们的社交和专业目的现在是很正常的。因此,从幼儿园的学生(在网上看儿歌和故事)到老年人(通过手机或电脑进行金融交易),几乎所有年龄段的人患DES(数字眼疲劳)或CVS(计算机视觉综合症)的几率都增加了几倍。在这两者之间,所有其他世代的人都在使用数字设备来达到某种目的。由于数字设备在各个年龄段都很受欢迎,所以所有年龄段都需要这种“智能护目镜”,以便在早期发现他们的DES。
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Smart Goggle: A Device to ascertain DES (Digital Eye Strain)
Objective: This invention is very useful in the current scenario, where Digital Eye Strain (DES) is a common delinquent among people that using digital devices for more than permissible time. The objective behind this invention to ascertain DES at regular intervals or at an early stage so that required remedial solutions can be taken or reversals can be executed to save our eyes. Background: The device is based on the system that will detect eye strain symptom like traceable (Eye blinking rate, Redness in eyes, eye squeezing and eye itching) and non-traceable (Eye Pain, Watery eyes, blurred vision, headache) symptoms due to continuous use of digital devices and generate an alert if these symptoms are present. The system is now installed in a device to identify the strain. Device is called “Smart Goggle”. Method: The system is executed through various steps. Firstly, the system captures the video through camera and store in a module. The video will be divided into frames. The system will check the presence of traceable (Blink Rate, Redness, Squeezing, and Itching) factors in frames. If one of the traceable factor is present then system will check for another input to get non traceable (Eye Pain, Watery Eyes, Blurred vision and headache) factor from the user through input. Both the inputs are then passed into Machine Learning algorithm (Bayesian classification) to predict the eye strain. If eye strain is predicted by the classifier, then an alert is sent on user’s machine to intimate about eye strain status Application: The use of digital devices to execute their social and professional purposes is now quite normal. Due to this, occurrence of DES (Digital Eye Strain) or CVS (Computer Vision Syndrome) has increased few folds in almost all generations from the kinder garden student (who watches rhymes and stories online) to a senior citizen (who executes its financial transactions through mobile or computer). Between these two all other generations are using digital devices for some or the other purposes. As digital devices are very popular among all ages so there is a need of this “Smart Goggle” among all age groups to detect their DES at early stage.
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