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Brain wave analysis method and terminal

An analysis method and brain wave technology, applied in the field of data processing, can solve problems such as inappropriate classification, loss of change details, and lack of focus

Active Publication Date: 2021-07-30
深湾创新技术(深圳)有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, pressure should be a process of continuous change. Simply summarizing the pressure into several levels will lose a lot of change details.
And because there are individual differences, the same characteristic may be focused for some people and inattentive for others, and it is not appropriate to use the same model to classify the status of all people.

Method used

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  • Brain wave analysis method and terminal
  • Brain wave analysis method and terminal
  • Brain wave analysis method and terminal

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0059] Please refer to figure 1 , a method for analyzing brain waves, comprising the steps of:

[0060] S1. Obtain the resting state data of brain waves of the object to be analyzed;

[0061] Specifically, the brain wave data of the subject to be analyzed is collected through a portable brain wave headband such as the DBay EEG headband; the frequency of this device is 250 Hz, and there are 5 electrodes distributed horizontally on the forehead; from left to right are AF7 electrodes , a first drive electrode, a reference electrode, a second drive electrode, and an AF8 electrode; wherein, the first drive electrode and the second drive electrode are physically connected structures for removing noise and reducing environmental interference noise; through the AF7 electrode and the AF8 electrode Two channels of EEG signals are collected, which are the AF7 signal of the left forehead and the AF8 signal of the right forehead; in this collection state, the subject to be analyzed will n...

Embodiment 2

[0085] The difference between this embodiment and Embodiment 1 is that further processing is performed on the acquired brain wave test data of the object to be analyzed;

[0086] After the acquisition of the brain wave test data of the object to be analyzed includes:

[0087] Converting the obtained brain wave test data of the object to be analyzed into the power spectral density of the brain wave signal; obtaining the energy values ​​of different types of brain waves according to the power spectral density of the brain wave signal; according to the different types of brain wave The energy value generates the corresponding brain wave characteristic curve;

[0088] Specifically, since the feature analysis of EEG is mostly based on the frequency domain, the time domain signal is first converted into a frequency domain signal; the main conversion methods are fast Fourier transform (fastFourier transform, FFT) and wavelet transform, transform The final signal is the power spectru...

Embodiment 3

[0110] Please refer to Figure 4 , an electroencephalogram analysis terminal, comprising a memory, a processor, and a computer program stored on the memory and operable on the processor, when the processor executes the computer program, the method described in Embodiment 1 or Embodiment 2 is realized Various steps of a brain wave analysis method;

[0111] Specifically, please refer to Figure 5 , including 8 modules: signal acquisition module, signal transmission module, abnormal signal detection module, preprocessing module, feature calculation and its combination module, baseline acquisition module, index quantification module and real-time score;

[0112] The signal acquisition module is used to collect brainwave data; the signal transmission module is used to transmit brainwave data to a processing terminal; the abnormal signal detection module is used to detect abnormal signals in the brainwave data collection process; the The preprocessing module is used to remove nois...

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Abstract

The invention discloses a brain wave analysis method and a terminal. The method comprises the following steps: obtaining brain wave resting state data of a to-be-analyzed object, generating a data threshold value of a resting baseline state, obtaining the data threshold value of the resting baseline state according to the resting state data, obtaining a scaled model, carrying out brain wave test on the to-be-analyzed object, scaling the brain wave test data of the to-be-analyzed object through the scaled model, obtaining a scaled curve of the brain wave test data, and determining the state of the to-be-analyzed object according to the scaled curve. Therefore, the to-be-analyzed object can know the mental state of each moment in the test process through the scaled brain wave data, and meanwhile, the brain wave data of each to-be-analyzed object can generate a quantitative curve corresponding to the individual to-be-analyzed object, so that the difference of test data between individuals is eliminated, different to-be-analyzed objects can judge the mental state according to the scaled curve, and the accuracy of brain wave analysis is improved.

Description

technical field [0001] The invention relates to the field of data processing, in particular to a brain wave analysis method and a terminal. Background technique [0002] With the continuous upgrading of electroencephalogram (Electroencephalogram, EEG) signal acquisition and recognition technology, real-time EEG monitoring technology is becoming more and more mature. By obtaining the corresponding brain wave signal characteristics, some mental states of the human body can be judged, such as concentration, stress, relaxation, fatigue and other mental states. EEG features are mainly related to the time domain and frequency domain, and the time domain features mainly include the correlation and mean square value of the two signals. The frequency domain features mainly include brain waves in various frequency bands, including band energy such as Delta, Theta, Alpha, Beta, and Gamma, as well as features such as coherence and sample entropy. However, most of the characteristics d...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/369A61B5/372A61B5/16
CPCA61B5/7203A61B5/7225A61B5/168A61B5/7235
Inventor 熊秀春周可忠梁红波
Owner 深湾创新技术(深圳)有限公司