Intelligent myopia prevention system and method based on AI learning

Abstract

The invention discloses an intelligent myopia prevention system based on AI learning. The system is provided with an eye behavior monitoring unit, wherein the eye behavior monitoring unit comprises adistance sensor and an acceleration sensor; an MCU central processing unit which is used for receiving and processing eye data sent back by a sensing unit is arranged in a device body; a server is used for interacting and transmitting data with the MCU central processing unit, and learning the eye data sent back by a large number of users to continuously optimize algorithms; a mobile terminal is further arranged between a wireless signal transceiver and the server; and the mobile terminal displays an analysis result of the eye data of the server to a user and interacts with the MCU central processing unit and the server respectively under the control of the user. According to the system, various variables related to eye habits can be quantitatively detected, a big data technology and artificial intelligence learning are utilized to continuously optimize the algorithms, the eye habits can be comprehensively analyzed and deviation rectification can be carried out from a plurality of dimensions, and the user can be reminded to gradually correct the bad eye habits.

Description

technical field [0001] The present invention relates to the field of health, in particular to an intelligent anti-myopia system and method based on AI learning. Background technique [0002] It is estimated that about 2.5 billion people in the world are affected by myopia, and as many as 90% of young people in my country suffer from myopia. Bad eye habits are an important cause of myopia. [0003] The patent with the Chinese patent announcement number CN106023543A discloses a method for preventing and controlling myopia posture for students. Its prevention and control method is as follows: Step 1: Connect the distance detection device to the head; The data displayed on the screen sets the data range, and the display screen is placed on the desktop. Step 3: Detect the sitting posture; Step 4: Data storage, when the distance sensor and the tilt sensor transmit the data to the processor, the processor stores the data, and at the same time The data is uploaded to the host compu...

AI Technical Summary

Problems solved by technology

[0004] The above-mentioned technology has the following disadvantages: the source of eye data collection is single, and the eye posture, head movement rate changes, head tilt angle, angle between line of sight and horizontal plane and other related eye conditions cannot be checked at the same time. The method of judging whether it is healthy to use eyes by sitting posture cannot avoid other unhealthy ways to use eyes, such as squinting, shaking legs, reading while lying down or walking, etc. The judgment of healthy eyes needs to be based on multi-dimensional detection of user's eye habits

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