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Applying neural network analysis on heart rate variability data to assess driver fatigue

Applying neural network analysis on heart rate variability data to assess driver fatigue,10.1016/j.eswa.2010.12.028,Expert Systems With Applications,M

Applying neural network analysis on heart rate variability data to assess driver fatigue  
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Long duration driving is a significant cause of fatigue related accidents on motorways. Fatigue caused by driving for extended hours can acutely impair driver’s alertness and performance. This papers presents an artificial intelligence based system which could detect early onset of fatigue in drivers using heart rate variability (HRV) as the human physiological measure. The detection performance of neural network was tested using a set of electrocardiogram (ECG) data recorded under laboratory conditions. The neural network gave an accuracy of 90%. This HRV based fatigue detection technique can be used as a fatigue countermeasure.
Journal: Expert Systems With Applications - ESWA , vol. 38, no. 6, pp. 7235-7242, 2011
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