Emotion and fatigue detecting auxiliary driving system based on hybrid brain computer interface technology

Abstract

The invention discloses an emotion and fatigue detecting auxiliary driving system based on hybrid brain computer interface technology. The system comprises the components of a brain electric signal acquisition part, a brain electric signal processing and analyzing part, a fatigue alarming and voice control on-vehicle electric appliance part. The brain electric signal acquisition part acquires an analog amount brain electric signal and outputs the signal to the brain electric signal processing part. The brain electric signal processing part performs processing on the brain electric signal, calculates a driver fatigue degree and further transmits a result to the fatigue alarming and voice control on-vehicle electric appliance part. The fatigue alarming and voice control on-vehicle electric appliance part performs corresponding alarming according to the obtained result and further transmits the alarm to an electric appliance/equipment control module for controlling on-vehicle electric appliance/equipment. The emotion and fatigue detecting auxiliary driving system performs detection on a fatigue and emotion condition of a driver in a driving process and eliminates a potential safety hazard which is generated by the driving fatigue and road rage driving, thereby reducing generation rate of traffic accidents, realizing auxiliary voice control on equipment such as air conditioner, multimedia equipment and sunroof, and improving driving safety.

Description

technical field [0001] The invention relates to the combined application field of neuroscience and information technology, in particular to an auxiliary driving system of signal processing, neural control and automatic control. Background technique [0002] With the development of the transportation industry and the automobile industry, traffic accidents have become a serious problem facing all countries. my country is a country with a high incidence of road traffic accidents. According to incomplete statistics, there were 196,812 and 198,394 road traffic accidents in 2014 and 2015, respectively, and the death toll was 58,523 and 58,539, causing huge casualties and property losses; A considerable number of traffic accidents in these accidents are caused by driver factors, such as driver drunk driving, driving fatigue, and mood swings. Among them, traffic accidents caused by driver fatigue account for about 15% of all traffic accidents, and road traffic safety has increasingl...

AI Technical Summary

Problems solved by technology

These products use visual processing to detect the state of the driver's face and eyes, or detect the driver's myoelectric signal and control the physical quantity of the car steering wheel to judge the driver's fatigue and emotional changes. The application of visual processing has many limitations and the physical quantity is limited. Analysis cannot accurately reflect the driver's mental state

In order to improve the accuracy of detecting driver fatigue and emotional changes during driving, CHIN-Teng Lin from the University of California, San Diego, and others took the lead in extracting a method to analyze driver fatigue based on EEG signals, followed by many domestic research teams Driver fatigue and emotion analysis based on EEG signals has also begun, but the existing analysis is only at the laboratory stage, and the practicability needs to be improved. At present, there is no perfect commercial driver fatigue detection and emotion based on EEG analysis. analysis system

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