A method and system for monitoring and warning of fatigue driving

By combining multiple indicators such as EEG signals, blood oxygen saturation, and eye closure index for fusion analysis, the problem of misjudgment caused by single detection methods is solved, enabling accurate monitoring and reasonable early warning of driver fatigue, thus improving detection accuracy and safety.

CN115177255BActive Publication Date: 2026-07-07FOSHAN UNIVERSITY
View PDF 0 Cites 0 Cited by

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
FOSHAN UNIVERSITY
Filing Date
2022-05-25
Publication Date
2026-07-07

AI Technical Summary

Technical Problem

Existing fatigue detection methods cannot accurately reflect the driver's fatigue state and are at risk of misjudgment, especially in complex environments, particularly at night or when the driver is wearing a mask, resulting in low detection accuracy.

Method used

By combining EEG signals, blood oxygen saturation, and eye closure index, a driver fatigue state decision function is established. The driver's EEG signals, emitted light intensity signals from the prefrontal cortex, and recorded video of the human eye are collected. These signals are processed to obtain the index MI, blood oxygen saturation SrO2, and eye closure index EI. Feature fusion is performed through canonical correlation analysis, and support vector machine is used to determine the fatigue level and issue an early warning.

Benefits of technology

It enables real-time monitoring and accurate judgment of driver fatigue status, and can issue reasonable and humane warnings based on fatigue level, thereby improving detection accuracy and reducing misjudgments.

✦ Generated by Eureka AI based on patent content.

Smart Images

  • Figure CN115177255B_ABST
    Figure CN115177255B_ABST
Patent Text Reader

Abstract

The application is suitable for the field of fatigue driving detection, and discloses a fatigue driving monitoring and early warning method and system, which can monitor the fatigue state of a driver in real time. The method collects the brain electrical signals of the driver, the outgoing light intensity signals of the frontal lobe area, and the video recorded by the human eye; processes the collected data to obtain indexes such as the index MI for measuring the fatigue degree of the driver, the blood oxygen saturation SrO2, and the eye closure index EI, judges the fatigue driving through multiple indexes, can improve the monitoring accuracy, then analyzes the comprehensive fatigue index and the eye closure index EI according to the driver fatigue state decision function, judges and grades the fatigue driving of the driver, and if it is judged that the driver is in the fatigue driving state, different degrees of early warning are sent to the driver based on different fatigue grades, and the early warning mechanism is more reasonable and humanized.
Need to check novelty before this filing date? Find Prior Art