A method for processing EEG signals based on the diva model

A technology of EEG signals and processing methods, which is applied in the fields of electrical digital data processing, special data processing applications, medical science, etc., and can solve problems such as low signal resolution, low signal-to-noise ratio, and high post-processing requirements.

Active Publication Date: 2017-01-25
西安慧脑智能科技有限公司
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Problems solved by technology

Although this non-invasive device is convenient to wear on the human body, the resolution of the recorded signal is not high due to the attenuation effect of the skull on the signal and the dispersion and blurring effect on the electromagnetic waves emitted by the neurons.
This kind of signal wave can still be detected, but the signal-to-noise ratio is low, and the requirements for post-processing are high

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  • A method for processing EEG signals based on the diva model
  • A method for processing EEG signals based on the diva model
  • A method for processing EEG signals based on the diva model

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[0080] Step 1. Extract the electroencephalogram signal (EEG) during the pronunciation of the Chinese vowel ɑ through a non-invasive brain-computer interface. Preprocessing the collected EEG data, including removal of blink artifacts, eye movement artifacts, low-pass filtering, bad electrode reset, averaging and baseline correction;

[0081] Step 2. Based on the user interface provided by the DIVA model, the first three formant frequencies are set to 805Hz, 1265Hz and 2770Hz, so that the model performs simulated pronunciation of the Chinese vowel ɑ to obtain fMIR data. Then, the data results generated by the simulation were input into the statistical drawing tool SPM for analysis, and the data were normalized by the affine transformation with 12 parameters. The image is then registered with the high-resolution structural image and normalized to the MNI space. Then use a three-dimensional Gaussian function with a full width at half maximum (FWHM) of 12mm*12mm*24mm to perform sp...

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Abstract

The invention discloses an electroencephalogram signal processing method based on a DIVA model. According to the electroencephalogram signal processing method, fMIR data generated through the DIVA model in a simulating mode are used for carrying out positioning analysis on electroencephalogram signals, the complexity of actual computing is simplified through an independent component analysis method, and the defects that non-intrusive electroencephalogram signals are low in resolution ratio and high in interference are overcome. The fMIR data generated through the DIVA model are used for carrying out fusion processing on electroencephalogram data, and the problems that the electroencephalogram signals are low in space resolution ratio, high in signal interference and low in signal-noise ratio are resolved greatly. Through the pre-processing of ICA, the computing complexity is reduced, and the sensitivity of an equivalent dipole positioning algorithm to the noise is overcome greatly. Finally, the electroencephalogram signal processing method is used for processing actual experiment data, and the obtained conclusion meets the physiology reality. A feasible resolution scheme is provided for the electroencephalogram signal processing problem in a Chinese nerve analysis system, and a foundation is laid for the research related to generation and obtaining of Chinese phonetic symbols in future.

Description

technical field [0001] The invention discloses a method for processing electroencephalogram signals based on a DIVA model, and relates to the technical field of electroencephalogram signal processing. Background technique [0002] Brain-computer interface (brain computer interface, BCI) is a system based on EEG signals to realize communication and control between the human brain and computers or other electronic devices. channel communication system. In other words, BCI is a direct communication and control channel established between the human brain and the computer. Through this channel, people can express ideas or manipulate devices directly through the brain without language or body movements. [0003] A research team led by Professor Frank Guenther of Boston University has successfully developed a neural analysis system (Neuralynx System) based on brain-computer interface technology. The neural analysis system consists of two parts: the brain-computer interface (BCI) ...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): A61B5/0476G06F17/50
CPCA61B5/316
Inventor 张少白陈彦霖
Owner 西安慧脑智能科技有限公司
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