Memory state evaluation method, system, device and storage medium

Abstract

The present invention discloses a memory state evaluation method, system, device and storage medium. The method comprises the following steps of issuing a memory state evaluation item, collecting an event-related brain potential, analyzing and processing the event-related brain potential in a pre-trained convolutional neural network, and displaying a memory state evaluation result and pushing a learning item according to a result obtained by the analyzing and processing. The system comprises a testing module, an acquisition module, a training module, a processing module and a pushing module. The used memory state evaluation method can more accurately and effectively reflect a memory state of a person, better guides daily life and work of the person, meanwhile, can also reduce data appliedin analysis, accelerates analysis processes, and can be widely applied in the technical field of deep learning.

Description

technical field [0001] The present invention relates to the technical field of deep learning, in particular to a memory state evaluation method, system, device and storage medium. Background technique [0002] Memory is the most basic learning ability of human beings, and the mastery and application of any high-level technology and knowledge are based on this foundation. However, people often have inaccurate judgments on their own memory ability and the accuracy of the items they remember. There is great subjectivity and instability, and it is difficult to truly reflect one's own memory state, so it is impossible to respond and adjust in a targeted manner. [0003] On the other hand, some existing technical solutions use EEG memory rhythm waves to characterize and evaluate people's memory status, but the EEG signals extracted in this way are very redundant and complex, and they are the overall brain waves of people when they are thinking. , the evaluation results are often...

AI Technical Summary

Problems solved by technology

However, people often have inaccurate judgments on their own memory ability and the accuracy of the items they remember. There is great subjectivity and instability, it is difficult to truly reflect one's own memory state, and it is impossible to respond and adjust in a targeted manner

[0003] On the other hand, some existing technical solutions use EEG memory rhythm waves to characterize and evaluate people's memory status, but the EEG signals extracted in this way are very redundant and complex, and they are the overall brain waves of people when they are thinking. , the evaluation results are often general, it is difficult to truly and accurately reflect the real memory state of the person, and the analysis efficiency is very low

Therefore, whether it is based on the individual's own subjective judgment or the evaluation of memory status through EEG memory rhythm waves, it is impossible to give results with good reference value and related suggestions.

In the prior art, there is no good technical solution that can effectively solve the drawbacks in the above-mentioned fields

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