Mental Fatigue Electroencephalogram Signals Analysis Based on Singular System_Journal of Biomedical Engineering

Authors：

 ZHANGChong , YUXiaolin , YANGYong , XULei

Department of Information Engineering, Officers College of CAPF, Chengdu 610213, China;

Corresponding author：

ZHANGChong, Email: xlyu.czhang@gmail.com

Keywords：

mental fatigue; electroencephalogram; singular system analysis; the largest principal component

DOI：

10.7507/1001-5515.20140213

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In the present paper, the contribution of the largest principal component and the number of principal component needed for accumulative contribution 95% are selected as indices of electroencephalogram (EEG) in mental fatigue state in order to investigate the relationship between these parameters and mental fatigue. The experimental results showed that the contribution of the largest principal component of EEG signals increased in the prefrontal, frontal and central areas, while the number of principal component needed for accumulative contribution decreased by 95% with the increasing mental fatigue level. The parameters of singular system of EEG signals can be regarded as useful features for the estimation of mental fatigue and have larger application value in the study of mental fatigue.

Citation： ZHANGChong, YUXiaolin, YANGYong, XULei. Mental Fatigue Electroencephalogram Signals Analysis Based on Singular System. Journal of Biomedical Engineering, 2014, 31(5): 1132-1134,1138. doi: 10.7507/1001-5515.20140213 Copy

1.	YANG B, XIAO W, LIU X F, et al. Mental fatigue impairs pre-attentive processing:a MMN study[J]. Neurosci Lett, 2013, 532(4): 12-16.
2.	胡文东,马进,韩文强.飞行疲劳的预防和监测手段[J].中国临床康复,2004,8(3):542-543.
3.	LIM J, QUEVENCO F C, KWOK K. EEG alpha activity is associated with individual differences in post-break improvement[J]. Neuroimage, 2013, 76(1): 81-89.
4.	LIN C F, ZHU J D. Hilbert-Huang transformation-based time-frequency analysis methods in biomedical signal applications[J]. Proc Inst Mech Eng H, 2012, 226(3): 208-216.
5.	HUANG N E, SHEN Z, LONG S R. A new view of nonlinear water waves: the Hilbert spectrum[J]. Annu Rev Fluid Mech, 1999, 31: 417-457.
6.	PACHORI R B, BAJAJ V. Analysis of normal and epileptic seizure EEG signals using empirical mode decomposition[J]. Comput Methods Programs Biomed, 2011, 104(3): 373-381.
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8.	LIU J P, ZHANG C, ZHENG C X. Estimation of the cortical functional connectivity by directed transfer function during mental fatigue[J]. Appl Ergon, 2010, 42(1): 114-121.
9.	刘建平,张崇,郑崇勋,等.基于多导脑电复杂性测度的脑疲劳分析[J].西安交通大学学报,2008,42(12):1555-1559.
10.	VIDULICH M A. The mental psychology of subjective mental workload[M]//HANCOCK P A, MESHKATI N. Human mental workload. Amsterdam: North-Holland, 1988: 219-229.

1. YANG B, XIAO W, LIU X F, et al. Mental fatigue impairs pre-attentive processing:a MMN study[J]. Neurosci Lett, 2013, 532(4): 12-16.
2. 胡文东,马进,韩文强.飞行疲劳的预防和监测手段[J].中国临床康复,2004,8(3):542-543.
3. LIM J, QUEVENCO F C, KWOK K. EEG alpha activity is associated with individual differences in post-break improvement[J]. Neuroimage, 2013, 76(1): 81-89.
4. LIN C F, ZHU J D. Hilbert-Huang transformation-based time-frequency analysis methods in biomedical signal applications[J]. Proc Inst Mech Eng H, 2012, 226(3): 208-216.
5. HUANG N E, SHEN Z, LONG S R. A new view of nonlinear water waves: the Hilbert spectrum[J]. Annu Rev Fluid Mech, 1999, 31: 417-457.
6. PACHORI R B, BAJAJ V. Analysis of normal and epileptic seizure EEG signals using empirical mode decomposition[J]. Comput Methods Programs Biomed, 2011, 104(3): 373-381.
7. 刘建平,郑崇勋,张崇.基于非线性回归系数的中枢疲劳脑电的幅度耦合分析[J].中国医疗器械杂志,2009,33(4):259-261.
8. LIU J P, ZHANG C, ZHENG C X. Estimation of the cortical functional connectivity by directed transfer function during mental fatigue[J]. Appl Ergon, 2010, 42(1): 114-121.
9. 刘建平,张崇,郑崇勋,等.基于多导脑电复杂性测度的脑疲劳分析[J].西安交通大学学报,2008,42(12):1555-1559.
10. VIDULICH M A. The mental psychology of subjective mental workload[M]//HANCOCK P A, MESHKATI N. Human mental workload. Amsterdam: North-Holland, 1988: 219-229.

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