Method for detecting driving fatigue based on electroencephalogram

A technology for EEG signals and driving fatigue, applied in diagnostic signal processing, electrical digital data processing, diagnostic recording/measurement, etc.

Active Publication Date: 2017-02-01
CHONGQING JINOU SCI & TECH DEV
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Problems solved by technology

Support vector machine is one of the commonly used methods. Although it can achieve good results in practical applications, it needs to use the

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  • Method for detecting driving fatigue based on electroencephalogram
  • Method for detecting driving fatigue based on electroencephalogram
  • Method for detecting driving fatigue based on electroencephalogram

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Embodiment Construction

[0113] The present invention is further described above in conjunction with the accompanying drawings and specific embodiments.

[0114] (1) Select the feature quantities related to the fatigue driving state: feature selection refers to a feature set composed of a group of related feature quantities obtained after a series of corresponding processing on the original measurement signal, and then select some features from the feature set. The representative physical quantity with the best classification performance is used as a set of feature quantities to distinguish different behaviors, and then the relevant classification recognition method is used to separate different behaviors from the feature space by using the selected feature quantities. Therefore, for learning classification Both require training set samples:

[0115] T={(x 1 ,y 1 ),…,(x l ,y l )}∈(X×Y) l (1)

[0116] where x i ∈X=R n ,y i ∈Y=R,i=1,...,l;

[0117] For the training set that meets the requirem...

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Abstract

The invention relates to a method for detecting driving fatigue based on electroencephalogram. The method specifically comprises the following steps: (1) selecting characteristic quantity related to a driving fatigue state; (2) performing electroencephalogram power spectrum analysis on the driving fatigue state; (3) performing electroencephalogram sample entropy analysis on the driving fatigue state; (4) performing electroencephalogram Kc complexity analysis on the driving fatigue state; (5) using support vector machine (SVM); (6) using least squares support vector machine (LS-SVM); (7) setting model training parameters (C and g) through a particle swarm optimization (PSO) algorithm. According to the method disclosed by the invention, electroencephalograms extracted in different driving states are respectively researched from a power spectrum angle by using related methods in non-linear dynamics, so that excellent effects can be achieved in accuracy and reliability.

Description

technical field [0001] The invention belongs to the technical field of traffic driving, in particular to a method for detecting driving fatigue based on electroencephalogram signals Background technique [0002] How to select the appropriate feature quantity from many features closely related to the fatigue state plays a very important role in the accurate identification of driving fatigue. After correlative processing of the EEG signal, the selected relevant feature vectors are obtained, and then some classifiers are used to make discrimination based on these feature vectors. Support vector machine is one of the commonly used methods. Although it can achieve good results in practical applications, it needs to use the quadratic programming method to solve it. When the number of samples is relatively large, it needs to consume a lot of memory and computing time. . The present invention studies the extracted EEG signals of different driving states from the perspective of pow...

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Application Information

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IPC IPC(8): G06F3/01G06K9/62A61B5/00
CPCG06F3/015A61B5/72G06F2203/011A61B2503/22G06F18/2411
Inventor 金纯
Owner CHONGQING JINOU SCI & TECH DEV
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