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Fatigue driving detection method based on electroencephalogram signals

An EEG signal, fatigue driving technology, applied in diagnostic recording/measurement, medical science, instruments, etc., can solve problems such as affecting driving safety and interfering with the normal operation of drivers, and achieve the effect of accurate and objective judgment.

Active Publication Date: 2017-03-15
广西华泰国际货运代理有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Although the measurement of physiological signals needs to be in contact with the human body, the detection equipment will interfere with the normal operation of the driver and affect driving safety
Moreover, due to individual differences, the physiological signal characteristics of different people will be different, and some of them are quite different, so there are great limitations

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  • Fatigue driving detection method based on electroencephalogram signals
  • Fatigue driving detection method based on electroencephalogram signals
  • Fatigue driving detection method based on electroencephalogram signals

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Embodiment Construction

[0044] The following specific examples further illustrate the present invention, but are not intended to limit the present invention.

[0045] A method for detecting fatigue driving based on EEG signals, comprising the following steps:

[0046] S1: Collect the EEG signal of the driver while driving in real time, and perform the process of removing blink artifacts to obtain the EEG brain wave signal;

[0047] S1-1: Perform ICA on the EEG signal to obtain N independent components and a mixing matrix A;

[0048] S1-2: Calculate the CBI(j) of each component;

[0049] S1-3: Find out the largest component of CBI and use it as a candidate component;

[0050] S1-4: Check whether the candidate component satisfies the relevant conditions, if so, it is an eye blinking component, otherwise it is not;

[0051] S1-5: After determining the blink component, set the column of coefficients corresponding to the blink component in matrix A to zero, and then reconstruct the signal;

[0052] S2...

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Abstract

The invention discloses a fatigue driving detection method based on electroencephalogram signals, comprising the following steps: S1, collecting the electroencephalogram signals of a driver in real time during driving, and removing blink artifacts to get EEG brain wave signals; S2, converting the EEG brain waves of the time-domain signals to a frequency domain, calculating the energy value of the feature wave in each frequency domain section in the brain waves, and determining the fatigue degree according to the amount of relative energy; S3, designing a BP neural network classifier to identify the feature signal of the fatigue degree; and S4, estimating the fatigue index and the fatigue degree. According to the fatigue driving detection method based on electroencephalogram signals put forward by the invention, the fatigue degree of a driver is judged in real time by analyzing the electroencephalogram rhythm of spontaneous electroencephalogram signals, and judgment is accurate, objective and direct.

Description

technical field [0001] The invention relates to the field of fatigue driving detection, in particular to a method for detecting fatigue driving based on electroencephalogram signals. Background technique [0002] In recent years, the number of motor vehicles and drivers has continued to increase, but the concept of traffic safety in society is obviously lagging behind, and road traffic safety is facing many challenges. In order to prevent fatigue driving, my country's traffic law stipulates that continuous driving for 4 hours is considered fatigue driving. However, since there are differences among individuals, it is necessary to take into account the differences in physique and living conditions of each driver. This time limit is difficult to grasp when implementing it. Therefore, it is necessary to study the mechanism and detection methods of fatigue driving. Fatigue driving detection methods are divided into the following three categories: detection methods based on faci...

Claims

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Application Information

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IPC IPC(8): G08B21/06A61B5/0476
CPCA61B2503/22A61B5/369G08B21/06
Inventor 胡克荣
Owner 广西华泰国际货运代理有限公司
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