Myopia prevention and control glasses and temples

Abstract

The invention provides myopia control glasses, comprising a frame and temples. Each temple includes a temple shell, and modules integrated in the temple shell, including: a data acquisition module foracquiring eye usage state data that at least include eye usage distance and light intensity data; a master control module for judging eye usage behaviors according to the eye usage state data and generating a reminding command; a reminding module for generating a reminding signal when the reminding command is received, so as to remind a user. The invention also provides a corresponding temple. Amyopia control function is integrated to the temples such that the myopia control glasses are the same as common glasses in appearance and is more helpful for use in various scenes; in addition, the myopia control glasses can track a user's eye usage data and provide real-time reminders upon bad habits in eye usage.

Description

technical field [0001] The technical field of electronic products of the present invention, in particular, relates to myopia prevention and control glasses and temples. Background technique [0002] Myopia glasses are a common consumer product used for myopia correction. But myopia glasses cannot prevent the deepening of myopia. And the occurrence and harm of myopia are irreversible. High myopia is prone to various types of fundus lesions, causing serious and permanent damage to visual function. The heritability and family aggregation of myopia will affect the quality of our population in the future. [0003] At present, there are some myopia prevention and control devices that remind people of eye behavior on the market. However, these devices often require additional detection devices to be installed on the glasses, such as cloud clips that are clipped above or outside the temples to monitor eye-using behavior. These additional detection devices usually affect the app...

AI Technical Summary

Problems solved by technology

[0005] Furthermore, because detection of traditional eye-use behavior data (eye distance, eye-use duration, and ambient light) can predict the current eye health and fatigue status to a certain extent, but these are external indicators of the human body, and each person's visual fatigue threshold are different, so it is difficult to accurately describe whether the current use status will cause visual fatigue

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