Autonomic learning intelligent adjustment headgear

Abstract

The invention discloses an autonomic learning intelligent adjustment headgear including: a headgear body, and a near-infrared collection module, a control circuit, a bone conduction earphone module and a power supply, which are installed on the headgear body. The near-infrared collection module includes a plurality of infrared sensors, which are uniformly distributed on the inner side of the headgear body in order to collect the concentrations of oxyhemoglobin and deoxyhemoglobin in cerebral cortex at prefrontal lobe of human body. The control circuit is connected to the near-infrared collection module for receiving the concentrations of the oxyhemoglobin and deoxyhemoglobin, is connected with the bone conduction earphone module, and controls the bone conduction earphone module to make different sounds according to the concentrations of the oxyhemoglobin and deoxyhemoglobin. The bone conduction earphone module is installed on the lower end of the headgear body to contact with the headof a user and send sounds. The power supply is used for supplying power. The autonomic learning intelligent adjustment headgear can control the bone conduction earphone module to make different soundsin order to alleviate fatigue or over-excitation of brain, thus regulating learning state.

Description

technical field [0001] The invention relates to an autonomous learning intelligent adjustment headgear, in particular to an autonomous learning method for controlling the bone conduction earphone module to emit different sounds according to the concentration signals of oxyhemoglobin and deoxygenated hemoglobin in the human prefrontal cerebral cortex to relieve human brain fatigue or excitement. Learn to adjust the headgear smartly. Background technique [0002] In the learning process, the learner is likely to affect the learning efficiency due to the learning state. For example, when the learner is exhausted, the learner is prone to physical and mental exhaustion, and the learning efficiency is low due to inattention. It is easy to be restless, and it is difficult to think calmly when encountering learning difficulties. Both of these situations will affect learning efficiency. [0003] Studies have shown that sound signals of different frequencies stimulate the human brain...

AI Technical Summary

Problems solved by technology

[0002] In the learning process, the learner is likely to affect the learning efficiency due to the learning state. For example, when the learner is exhausted, the learner is prone to physical and mental exhaustion, and the learning efficiency is low due to inattention. Easily restless and difficult to think calmly when encountering learning difficulties, both of which affect learning efficiency

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