Driver's drowsiness estimation by combining EEG signal analysis and ICA-based fuzzy neural networks

Chin Teng Lin, Sheng-Fu Liang, Yu Chieh Chen, Yung Chi Hsu, Li Wei Ko

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

The public security has become an important issue in recent years, especially, the safe manipulation and control of vehicles in preventing the growing number of traffic accident fatalities. Accidents caused by drivers' drowsiness have a high fatality rate due to the decline of drivers' abilities in perception, recognition, and vehicle control abilities while sleepy. Preventing such an accident requires a technique for detecting, estimating, and predicting the level of alertness of a driver and a mechanism to maintain the driver's maximum performance of driving. The ICAFNN is a fuzzy neural network (FNN) capable of parameter self-adapting and structure selfconstructing to acquire a small number of fuzzy rules for interpreting the embedded knowledge of a system from the given training data set. Our experiments show that the ICAFNN can achieve significant improvements in the accuracy of drowsiness estimation compared with our previous works.

Original languageEnglish
Title of host publicationISCAS 2006
Subtitle of host publication2006 IEEE International Symposium on Circuits and Systems, Proceedings
Pages2125-2128
Number of pages4
Publication statusPublished - 2006
EventISCAS 2006: 2006 IEEE International Symposium on Circuits and Systems - Kos, Greece
Duration: 2006 May 212006 May 24

Other

OtherISCAS 2006: 2006 IEEE International Symposium on Circuits and Systems
CountryGreece
CityKos
Period06-05-2106-05-24

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Electrical and Electronic Engineering

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    Lin, C. T., Liang, S-F., Chen, Y. C., Hsu, Y. C., & Ko, L. W. (2006). Driver's drowsiness estimation by combining EEG signal analysis and ICA-based fuzzy neural networks. In ISCAS 2006: 2006 IEEE International Symposium on Circuits and Systems, Proceedings (pp. 2125-2128). [1693037]