Bad learning posture detection and statistical display device and method

Abstract

Provided are a device and method for detecting, performing statistic and displaying adverse studying postures. The device comprises a processor, a calibrating button, a ferroelectric memory, a display screen, a motor, a head tracing and detecting unit, a first photosensitive sensor, a second photosensitive sensor, a first pressure sensor, and a second pressure sensor. The calibrating button, the ferroelectric memory, the display screen, the head tracing and detecting unit, the first photosensitive sensor, the second photosensitive sensor, the first pressure sensor, and the second pressure sensor are connected with the processor. The motor is connected with the head tracing and detecting unit. The head tracing and detecting unit is used for tracing and detecting the head of a user. The first photosensitive sensor and the second photosensitive sensor are used for detecting whether books are placed on a desktop. The first pressure sensor and the second pressure sensor are used for detecting whether the user places his / her hands on the desktop and the pressure on the desktop if yes. The device and the method are high in detection accuracy rate and low in cost, and may perform statistic and display adverse studying postures.

Description

technical field [0001] The invention relates to a bad learning posture detection and statistical display device and method. Background technique [0002] At present, the myopia rate of primary school students and junior high school students in my country has reached 34.6%, and the myopia rate of high school students has reached 70%. Myopia is caused by a variety of factors, the most important of which is the incorrect sitting posture of teenagers when studying, and the distance between the eyes and the homework is too close. For this reason, it is necessary to detect the sitting posture of adolescents and remind them through appropriate forms. [0003] At present, there are many devices and methods for sitting posture detection, mainly as follows: [0004] Relying on infrared ranging or ultrasonic sensors for detection (see CN201320751761, CN201320398679), when the distance value exceeds the threshold range, it is considered a bad learning posture, and it does not consider...

AI Technical Summary

Problems solved by technology

[0004] Relying on infrared ranging or ultrasonic sensors for detection (see CN201320751761, CN201320398679), when the distance value exceeds the threshold range, it is considered a bad learning posture, and it does not consider that the user may not be learning at this time, so it will often be falsely reported

[0005] Furthermore, the detection is based on the infrared ranging sensor. This type of detection method does not take into account the sitting height of the human body, so it is difficult to ensure that the sensor is facing the forehead of the human body, and the measured distance value cannot reflect most of the bad sitting postures with the head bowed or tilted left and right. There will be false negatives (missing negatives mean that bad learning postures are not detected, and there is no voice prompt for bad learning postures)

[0006] CMOS image sensor is used for detection (see CN201320006497), and its detection effect depends on image processing algorithm, which may easily lead to false positives and false positives in complex backgrounds (false positives mean bad learning postures are not detected accurately, and incorrect voice prompts appear), and higher cost

[0007] A pressure sensor is used to judge the learning state (see CN201120084030), but the judgment method also only uses an infrared sensor to judge the sitting posture, and there are also problems of false positives and false positives

[0008] In addition, the existing sitting posture detection method will send an audible and visual alarm after detecting a bad learning posture. However, during the learning process, the user will have a series of short-term actions such as drinking water, holding an eraser, flipping a schoolbag, thinking, etc., which will trigger an alarm.

Frequent alarms will greatly affect the user's learning attention and learning effect, and at the same time, it is easy to make them feel rebellious about it

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