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EEG-based driver fatigue evaluation
Topic – Drivers’ fatigue evaluation –(Use only journal articles)Approx 10 pages Report
Driver fatigue is a significant cause of traffic accidents and is believed to account for 20-30% of all vehicle accidents. The EEG signal has been shown to be one of the most predictive and reliable to describe an individual’s level of alertness. Using the driver fatigue database, develop a system to isolate EEG changes during early, medium and extreme phases of fatigue during driving.
What are the main aims of the project?
To design fatigue detectors/ develop algorithm
Literature Survey /Can you find any devices or software which could satisfy these aims?
Discuss and search articles for below methods and explain their drawback and why we think EEG is most reliable software compared to other.
PERCLOS (software) Percentage eye openness tracking
AVECLOS (Facial features tracking)
 Anti-Sleep Pilot (car features)
What are their main disadvantages?
How can you design a better system?
Compared to other softwares and devices EEG stands out far better. We will be workingon this component in our report.
Steps to design:
Find raw data (Google it please – EEG dataset for evaluation of driver fatique)
Open that data in MATLAB and read it
Process the data
Feature extraction (you have to decide what features you can choose and compare, choose as many features so the result will be accurate as this is a major report) alpha, beta, theta and delta waves of EEG an their Frequency, wavelength, energy, standard deviation
Statistics (use statically methods like standard deviation, and other parameters.)
Use MATLAB classifier (through which you will pass the features through)
Define and explain accordingly, for example – in the first hour driver not tired, in the second hour driver is tired)
Your observation based on that data.
Provide product specification and Block diagram and Feasibility of software

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