Driving fatigue electroencephalogram monitoring method based on stepped fatigue determination

Abstract

The invention discloses a driving fatigue electroencephalogram monitoring method based on stepped fatigue determination, comprising the steps: first, connecting devices and initializing parameters; second, acquiring electroencephalogram signals: using an electroencephalogram acquisition device to acquire and pretreat the electroencephalogram signals of a driver, and synchronously transmitting the pretreated electroencephalogram signals to an electroencephalogram signal monitor terminal; third, analyzing the electroencephalogram signals: analyzing the electroencephalogram signals acquired and pretreated within any second, and calling a stepped fatigue determination module to carry out analysis by a master control chip, wherein the process includes: synchronous storage of electroencephalogram signals, extraction of mediation degree and attention degree, determination of mediation degree corrected value and time corrected parameter, increase and decrease in fatigue step parameter, and judgment of driving fatigue. The method has simple steps and reasonable design, is convenient to implement and effective to use, can accurately monitor the driving fatigue state of a driver in a simple, quick and real-time manner and has high practical value.

Description

technical field [0001] The invention belongs to the technical field of electroencephalogram monitoring, and in particular relates to an electroencephalogram monitoring method for fatigue driving based on step fatigue judgment. Background technique [0002] With the development of my country's economy and society, the rapid growth of my country's highway road construction, the number of cars and drivers has also increased rapidly, which brings convenience to daily life. At the same time, frequent traffic accidents have also brought major social consequences loss. Nowadays, various technical means to reduce the occurrence of traffic accidents and reduce casualties have been applied. Currently, the most used fatigue detection method is the analysis of driver's driving behavior, that is, by recording and analyzing the driver's steering wheel, stepping on the brakes, etc. Behavior characteristics such as driver fatigue can be judged; however, this method is greatly affected by th...

AI Technical Summary

Problems solved by technology

Nowadays, various technical means to reduce the occurrence of traffic accidents and reduce casualties have been applied. Currently, the most used fatigue detection method is the analysis of driver's driving behavior, that is, by recording and analyzing the driver's steering wheel, stepping on the brakes, etc. and other behavioral characteristics to judge whether the driver is fatigued; however, this method is greatly affected by the driver's driving habits, and there is no unified, scientific and effective judgment theory to support it

Another type of fatigue detection method is to evaluate the fatigue of the driver's face and eye features through image analysis. This method uses the image acquisition and processing system to analyze whether the current driver is fatigued. It has certain real-time performance, but it is still not widely used. Applicability, because the biological characteristics of each person are different, and the external performance of some people's eyes does not represent the mental state at the moment, so there are also large errors; in addition, the current image acquisition and processing methods used in this method The system mainly includes ARM-based fatigue driving detection system, ear-mounted fatigue warning device, watch-t

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