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

Author(s)
Patel, M. Lal, S.K.L. Kavanagh, D. & Rossiter, P
Year
Abstract

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. (Author/publisher)

Publication

Library number
20120752 ST [electronic version only]
Source

Expert Systems with Applications, Vol. 38 (2011), No. 6 (June), p. 7235-7242, ref.

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This publication is one of our other publications, and part of our extensive collection of road safety literature, that also includes the SWOV publications.