Lempel-Ziv complexity changes and physiological mental fatigue level during different mental fatigue state with spontaneous EEG

Lian-Yi Zhang, Chong-Xun Zheng

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DOI: 10.4236/health.2009.11007                

Abstract

The objective was to study changes in EEG time-domain Kolmogorov complexity under different mental fatigue state and to evaluate mental fatigue using Lempel-Ziv complexity analysis of spontaneous EEG in healthy human subjects. EEG data for healthy subjects were acquired using a net of 2 electrodes (Fp1 and Fp2) at PM 4:00, AM 12:00 and AM 3:00 in the 24 hours sleep-deprived mental fatigue experiments. It was presented that initial results for eight subjects examined in three different mental fa-tigue state with 2-channel EEG time-domain Lempel-Ziv complexity computations. It was found that the value of mean Lempel-Ziv com-plexity corresponding to a special mental state fluctuates within the special range and the value of C(n) increases with mental fatigue increasing for the total frequency spectrum. The result in-dicates that the value of C(n) is strongly cor-relative with the mental fatigue state. These re-sults suggest that it may be possible to nonin-vasively differentiate different mental fatigue level according to the value of C(n) for particular mental state from scalp spontaneous EEG data. This method may be useful in further research and efforts to evaluate mental fatigue level ob-jectively. It may also provide a basis for the study of effects of mental fatigue on central neural system.

Keywords

Lempel-Ziv Complexity; Mental Fatigue; Spontaneous EEG; Circadiac Rhythm

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1]	T. F. Meijman, (1997) Mental fatigue and the efficiency of information processing in relation to work times, International Journal of Industrial Ergonomics, 20 (1), 31-38.
[2]	D. Linder, M. Frese, and T. F. Meijman, (2003) Mental fatigue and the control of cognitive process: Effects on perseveration and planning, Acta Psychologica, 113 (1), 45-65.
[3]	T. Akerstedt, A. Knustsson, P. Westterholm, et al., (2004) Men-tal fatigue, work and sleep, Journal of Psychosomatic Research, 57, 427-433.
[4]	R. Edwards, (1981) Human muscle function and fatigue, Ciba. Found. Symp., 82, 1-18.
[5]	F. Booth and D. Thomason, (1991) Molecular and cellular adaptation of muscle in response to exercise: perspectives of various models, Physiol. Rev., 71, 541-585.
[6]	S. C. Gandevia, (2002) Spinal and supraspinal factors in human muscle fatigue, Physiol. Rev., 81, 1725-1789.
[7]	R. B. Layzer, (1998) Asthenia and chronic fatigue syndrome, Muscle Nerve, 21(12), 1609-1611.
[8]	M. M. Lorist, (2000) Mental fatigue and task control: Planning and preparation, Psychophysiology, 37, 1-12.
[9]	D. E. Broadbent, (1979) Is a fatigue test possible now? The society lecture, Ergonomics, 12, 1277-1290.
[10]	D. H. Holding, (1983) Fatigue, In G. R. J. Hockey (ed), Stress and fatigue in human performance, New York: Wiley.
[11]	V. D. Gusev, V. A. Kulichkov, and O. M. Y. Chupakhina, (1991) Complexity analysis of genomes. I. Complexity and classification methods of detected structural regularities, Mol. Biol. (Mosk)., 25(6), 825-834.
[12]	V. D. Gusev, L. A. Nemytikova, and N. A. Chuzhanova, (1999) On the complexity measures of genetic sequences, Bioinformatics, 15(7), 994-999.
[13]	X. Chen, S. Kwong, and M. A. Li, (1999) Compression algorithm for DNA sequences and its applications in genome comparison, Genome Inform. Ser. Workshop Genome Inform., 10(1), 51-61.
[14]	A. Lempel and J. Ziv, (1976) On the complexity of finite se-quences, IEEE Trans. Inf. Theory, 22(1), 75-81.