tailieunhanh - Báo cáo hóa học: " Research Article Estimating VDT Mental Fatigue Using Multichannel Linear Descriptors and KPCA-HMM"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Estimating VDT Mental Fatigue Using Multichannel Linear Descriptors and KPCA-HMM | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2008 Article ID 185638 11 pages doi 2008 185638 Research Article Estimating VDT Mental Fatigue Using Multichannel Linear Descriptors and KPCA-HMM Chong Zhang Chongxun Zheng Xiaolin Yu and Yi Ouyang Key Laboratory of Biomedical Information Engineering of Education Ministry School of Life Science and Technology Xi an Jiaotong University 710049 Xi an China Correspondence should be addressed to Chongxun Zheng cxzheng@ Received 28 September 2007 Revised 23 December 2007 Accepted 21 February 2008 Recommended by Sergios Theodoridis The impacts of prolonged visual display terminal VDT work on central nervous system and autonomic nervous system are observed and analyzed based on electroencephalogram EEG and heart rate variability HRV . Power spectral indices of HRV the P300 components based on visual oddball task and multichannel linear descriptors of EEG are combined to estimate the change of mental fatigue. The results show that long-term VDT work induces the mental fatigue. The power spectral of HRV the P300 components and multichannel linear descriptors of EEG are correlated with mental fatigue level. The cognitive information processing would come down after long-term VDT work. Moreover the multichannel linear descriptors of EEG can effectively reflect the changes of 9 a and f waves and may be used as the indices of the mental fatigue level. The kernel principal component analysis KPCA and hidden Markov model HMM are combined to differentiate two mental fatigue states. The investigation suggests that the joint KPCA-HMM method can effectively reduce the dimensions of the feature vectors accelerate the classification speed and improve the accuracy of mental fatigue to achieve the maximum 88 . Hence KPCA-HMM could be a promising model for the estimation of mental fatigue. Copyright 2008 Chong Zhang et al. This is an open access article distributed under the .