Data visualization processing method and apparatus based on animal electroencephalogram identification

Abstract

The embodiment of the invention discloses a data visualization processing method and apparatus based on animal electroencephalogram (EEG) identification. The data visualization processing method basedon animal EEG identification includes the steps: acquiring original EEG signals of animal; removing the noise interference in the original EEG signals to obtain purified EEG signals; extracting the characteristic values in the purified EEG signals; according to a pre-constructed classification model, performing analysis and identification on the characteristic values so as to obtain the identification result of the animal psychological state; and displaying the identification result in a visualization mode. The data visualization processing method and apparatus based on animal EEG identification can accurately realize analysis and identification of EEG signals, and can extensively and vividly show the identification result of the EEG signals to the user in a visualization mode so as to realize a better human-computer interaction process in the exchange interaction mode to improve the user experience.

Description

technical field [0001] The invention relates to the field of brain-computer interface equipment, in particular to a data visualization processing method and device based on animal EEG recognition. Background technique [0002] In the field of brain-computer interface technology, the existing technology designs wearable devices for brain wave analysis based on human beings. Chinese patent document CN 105011932A discloses a fatigue driving EEG monitoring method based on meditation and concentration, using the concentration parameters and meditation parameters output by the TGAM chip, combined with the average value of the original EEG signal, to monitor the fatigue of the driver EEG signals are monitored. However, in the prior art, the concentration parameters and meditation parameters output by the TGAM chip can only calculate the brainwave parameters at a frequency of 1 Hz, and the changes in the brainwave state such as the mental state are often fleeting, requiring higher ...

AI Technical Summary

Problems solved by technology

However, in the prior art, the concentration parameters and meditation parameters output by the TGAM chip can only calculate the brainwave parameters at a frequency of 1 Hz, and the changes in the brainwave state such as the mental state are often fleeting, requiring higher time resolution to detect

[0003] In addition, in the prior art, the signal-to-noise ratio and reliability of the data after removing the electro-ocular noise in the original signal are low, and the removal of the electro-ocular noise in other prior art relies on principal component analysis and independent component analysis methods, which requires Separately set the electro-oculogram collecting electrodes located around the eyes, which increases the complexity of the equipment. At the same time, these two denoising methods require a long time, which is difficult to meet the real-time requirements

In the classification method, the use of PCA dimensionality reduction often leads to the loss of detailed information in the signal, making it difficult to capture subtle changes in mental state

[0004] Furthermore, the existing EEG analysis equipment or methods generally stop at obtaining the recognition results, that is, the existing EEG analysis equipment lacks human-computer interaction links, and cannot display the recognition result data in a rich and vivid manner.

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