SSVEP EEG classification method based on convolutional neural model augmented with EMD data

Abstract

The present invention relates to the algorithm of brain-computer interface, artificial intelligence and pattern recognition, more specifically, relates to the SSVEP EEG classification method based on the convolutional neural model enhanced by EMD data, which can be applied to the fields of medical equipment, human-computer interaction, robot control, etc. . This method first preprocesses the original EEG data. After preprocessing, the empirical mode decomposition method is used to decompose the original EEG data, and a large number of artificial EEG data that conform to the time-frequency domain characteristics of the original EEG signal are generated by mixing. The original EEG data is merged and used for parameter training of the neural network, so as to achieve the effect of effectively training network parameters with a small amount of EEG data. Finally, the complex Morlet wavelet transform is used to generate the EEG tensor, and the original time domain data is converted into a tensor dictionary integrating time domain, frequency domain and spatial information as the input of the neural network, and the convolutional neural network model is used to enhance the data. EEG training set for classification.

Description

SSVEP EEG Classification Method Based on EMD Data Augmented Convolutional Neural Model technical field The present invention relates to the algorithm of brain-computer interface, artificial intelligence and pattern recognition, more particularly, relate to based on EMD data The SSVEP EEG classification method of the enhanced convolutional neural model can be applied to medical devices, human-computer interaction, robot control, etc. field. Background technique In recent years, with the development of computer science and artificial intelligence technology, brain-computer interface technology (BCI) as a new It has important application value in the field of rehabilitation science and control. BCI uses EEG signals to realize the human brain Communication or control with a computer or other electronic device, so it can help physically disabled patients to Improve the ability to communicate with the outside world. Steady-state visual evoked potentials are currently a...

AI Technical Summary

Problems solved by technology

And at present, many researchers study EMD-based EEG data enhancement methods, but these studies are only used in the classification research of EEG data linear classifiers, and the EEG data enhancement method is only replacement, rather than generating new data for Expand the original training set

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