Fatigue driving monitoring system based on electroencephalogram signal, electronystagmogramsignal and electromyogram signal

Abstract

Disclosed is a fatigue driving monitoring system based on an electroencephalogram signal, an electronystagmogramsignal and an electromyogram signal, and relates to the technical field of safety driving monitoring of automobiles. The system comprises a signal collecting module, a signal processing module, a driving state judging module and an alarming module; the signal collecting module is used for collecting the electroencephalogram signal, the electronystagmogramsignal and the electromyogram signal separately; the signal processing module is used for processing the electroencephalogram signal, the electronystagmogramsignal and the electromyogram signal which are collected by the signal collecting module, processing and analyzing a collected original electroencephalogram signal, electronystagmogramsignal and electromyogram signal, and conducting comparison with the driving state of a driver in a normal state to obtain a fatigue driving threshold value; the driving state judging moduleis used for judging the driving state of the driver according to the fatigue driving threshold value; the alarming module gives an alarm for reminding when it is judged that the driver is in a fatigue driving state. By means of the system, with the normal driving state of the driver as a judgment criterion, the driving safety of the driver can be effectively improved, and the occurrence of traffic accidents is reduced.

Description

technical field [0001] The invention relates to the technical field of automobile safety driving monitoring, in particular to a fatigue driving monitoring system. Background technique [0002] With the improvement of people's living standards, cars have entered thousands of households, the number of drivers has increased rapidly, and road safety issues have become particularly prominent. Fatigue driving is an important cause of traffic accidents. How to monitor the driver's Driving status is particularly important. [0003] The methods of monitoring the driver’s driving state can be roughly divided into two categories. One is to use the driver’s face information collected by the camera to process it with a computer as a basis for judging whether the driver is fatigued or not. However, this type of monitoring is easily affected by light and requires Drivers cannot wear sunglasses, etc., and the monitoring rate is not high; the other is to use medical methods to monitor EEG s...

AI Technical Summary

Problems solved by technology

[0003] The methods of monitoring the driver’s driving state can be roughly divided into two categories. One is to use the driver’s face information collected by the camera to process it with a computer as a basis for judging whether the driver is fatigued or not. However, this type of monitoring is easily affected by light and requires Drivers cannot wear sunglasses, etc., and the monitoring rate is not high; the other is to use medical methods to monitor EEG signals to judge the driver's driving status. Although this type of monitoring is accurate, the driver experience is poor.

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