PL EN


Preferences help
enabled [disable] Abstract
Number of results
2010 | 16 | 2 | 67-84
Article title

Estimating mental fatigue based on electroencephalogram and heart rate variability

Content
Title variants
Languages of publication
EN
Abstracts
EN
The effects of long term mental arithmetic task on psychology are investigated by subjective self-reporting measures and action performance test. Based on electroencephalogram (EEG) and heart rate variability (HRV), the impacts of prolonged cognitive activity on central nervous system and autonomic nervous system are observed and analyzed. Wavelet packet parameters of EEG and power spectral indices of HRV are combined to estimate the change of mental fatigue. Then wavelet packet parameters of EEG which change significantly are extracted as the features of brain activity in different mental fatigue state, support vector machine (SVM) algorithm is applied to differentiate two mental fatigue states. The experimental results show that long term mental arithmetic task induces the mental fatigue. The wavelet packet parameters of EEG and power spectral indices of HRV are strongly correlated with mental fatigue. The predominant activity of autonomic nervous system of subjects turns to the sympathetic activity from parasympathetic activity after the task. Moreover, the slow waves of EEG increase, the fast waves of EEG and the degree of disorder of brain decrease compared with the pre-task. The SVM algorithm can effectively differentiate two mental fatigue states, which achieves the maximum classification accuracy (91%). The SVM algorithm could be a promising tool for the evaluation of mental fatigue.Fatigue, especially mental fatigue, is a common phenomenon in modern life, is a persistent occupational hazard for professional. Mental fatigue is usually accompanied with a sense of weariness, reduced alertness, and reduced mental performance, which would lead the accidents in life, decrease productivity in workplace and harm the health. Therefore, the evaluation of mental fatigue is important for the occupational risk protection, productivity, and occupational health.
Publisher

Year
Volume
16
Issue
2
Pages
67-84
Physical description
Dates
published
1 - 1 - 2010
online
5 - 5 - 2011
Contributors
author
  • The Commanders' College of the Armed Police Force, 110113 Shenyang, China
author
  • The Commanders' College of the Armed Police Force, 110113 Shenyang, China
References
  • Akerstedt T, Gillberg M. Subjective and objective sleepiness in the active individual. Int J Neurosci. 1990;52:29-37.[PubMed][Crossref]
  • Akselrod S, Gordon D, Maswed JB, Snidman N, Shannon DC, Cohen RJ. Hemodynamic regulation: investigation by spectral analysis. Am J Physiol. 1985;18:867-875.
  • Boksem MAS, Lorist MM, Meijman TF. Effects of mental fatigue on attention: an ERP study. Cognit Brain Res. 2005;25(1):106-117.
  • Boksem MAS, Meijman TF, Lorist MM. Mental fatigue, motivation and action monitoring. Biol Psychol. 2006;42(2):123-132.[Crossref]
  • Borg G. Borg's perceived exertion and pain scales. 1st ed. Champaign, IL: Human Kinetics; 1998. 120p.
  • Desmond PA, Hancock PA. Active and passive fatigue states. In: Hancock PA, Desmond PA, editors. Stress, workload, and fatigue. Mahwah, New Jersey: Lawrence Erlbaum Associates; 2001. p. 455-465.
  • Egelund N. Spectral analysis of heart rate variability as an indicator of driver fatigue. Ergonomics. 1982;25:663-672.[PubMed][Crossref]
  • Eoh HJ, Chung MK, Kim SH. Electroencephalographic study of drowsiness in simulated driving with sleep deprivation. Int J Ind Ergon. 2005;35(4):307-320.[Crossref]
  • Fisch BJ. Spehlmann's EEG Primer. 2nd rev. Amsterdam, The Netherlands: Elsevier Science BV; 1991.
  • Grandjean E. Fatigue in industry. Br J Intern Med. 1979;36:175-186.
  • Hayashi S, Minamitani H, Shin K. Assessment of autonomic function indicators of heart rate variability aimed to assess cumulative fatigue. In: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology; Oct 30-Nov 2; Chicago, Ill. IEEE Eng Med Biol. 1997. p.300-301.
  • Heller W, Nitschke JB, Etienne MA, Miller GA. Patterns of regional brain activity differentiate types of anxiety. J Abnorm Psychol. 1997;106(3):376-385.[PubMed][Crossref]
  • Hoddes E, Zarcone V, Smythe H, Phillips R, Dement W. Quantification of sleepiness: A new approach. Psychophysiology. 1973;10:431-436.[PubMed][Crossref]
  • Horne JA, Reyner LA. Driver sleepiness. J Sleep Res. 1995;4(1):23-29.[Crossref][PubMed]
  • Job RFS, Dalziel J. Defining fatigue as a condition of the organism and distinguishing it from habituation, adaptation, and boredom. In: Hancock PA, Desmond PA, editors. Stress, workload, and fatigue. Mahwah, New Jersey: Lawrence Erlbaum Associates; 2001. pp. 466-475.
  • Kecklund G, Akerstedt T. Sleepiness in a long distance truck driving: an ambulatory EEG study of night driving. Ergonomics. 1993;36:1007-1017.[Crossref]
  • Klimesch W. EEG alpha and theta oscillations reflect cognitive and memory performance: a review and analysis. Brain Res Rev. 1999;29(2-3):169-195.[Crossref]
  • Lal SKL, Craig A. A critical review of the psychophysiology of driver fatigue. Biol Psychol. 2001;55(3):173-194.[Crossref][PubMed]
  • Lal SKL, Craig A. Electroencephalography activity associated with driver fatigue: Implications for a fatigue countermeasure device. J Psychophysiol. 2001;15(1):183-189.[Crossref]
  • Lal SKL, Craig A. Driver Fatigue: Electroencephalography and Psychological Assessment. Psychophysiology. 2002;39(3):313-321.[Crossref][PubMed]
  • Li ZY, Jiao K, Chen M, Wang CT. Effect of magnitopuncture on sympathetic and parasympathetic nerve activities in healthy drivers - assessment by power spectrum analysis of heart rate variability. Eur J Appl Physiol. 2003;88(4-5):404-410.[PubMed][Crossref]
  • Li ZY, Wang C, Mak AF, Chow DH. Effects of acupuncture on heart rate variability in normal subjects under fatigue and non-fatigue state. Eur J Appl Physiol. 2005;94:633-640.[Crossref][PubMed]
  • Miyashita T, Ogawa K, Itoh H, Arai Y, Ashidagawa M, Uchiyama M et al. Spectral analyses of electroencephalography and heart rate variability during sleep in normal subjects. Auton Neurosci. 2003;103:114-120.[Crossref][PubMed]
  • Montano N, Ruscone TG, Porta A, Lombardi F, Pagani M, Malliani A. Power spectrum analysis of heart rate variability to assess the changes in sympathovagal balance during graded orthostatic tilt. Circulation. 1994;90:1826-1831.[PubMed][Crossref]
  • Murata A, Uetake A, Takasawa Y. Evaluation of mental fatigue using feature parameter extracted from event-related potential. Int J Ind Ergon. 2005;35(3):761-770.[Crossref]
  • Pagani M, Lombardi F, Guzzetti S, Rimoldi O, Furlan R, Pizzinelli P et al. Power spectral analysis of heart rate and arterial pressure variabilities as a marker of sympathovagal interaction in man and conscious dog. Circ Res. 1986;58:178-193.[Crossref]
  • Pang CCC, Upton ARM, Shine G et al. A comparison of Algorithms for Detection of Spikes in the Electroencephalogram. IEEE Trans Biomed Eng. 2003;50:521-526.[PubMed][Crossref]
  • Parati G, Saul JP, Di Rienzo M, Mancia G. Spectral analysis of blood pressure and heart rate variability in evaluating cardiovascular regulation. Hypertension. 1995;25:1276-1286.[PubMed][Crossref]
  • Pomeranz B, MacAuley RJB, Caudill MA, Kutz I, Adam D, Gordon D et al. Assessment of autonomic function in human by heart rate spectral analysis. Am J Physiol. 1985;17:151-136.
  • Samn SW, Perelli LP. Estimating aircrew fatigue: A technique with implications to airlift operations. Brooks AFB, TX: USAF School of Aerospace Medicine. Technical Report No. SAM-TR-82-21, 1982.
  • Scerbo M, Freeman FG, Mikulka PJ. A Biocybernetic System for Adaptive Automation. In: Backs RW, Boucsein W, editors. Engineering Psychophysiology: Issues and Applications. New Jersey: Lawrence Erlbaum Associates; 2000. p. 241-253.
  • Stern JA, Walrath LC, Goldstein R. The endogenous eyeblink. Psychophysiology. 1984;21(1):22-33.[Crossref][PubMed]
  • Stern JA, Boyer D, Schroeder D. Blink rate: a possible measure of fatigue. Hum Factors. 1994;36(2):285-297.
  • Task Force of the European Society of Cardiology the North American Society of Pacing Electrophysiology. Heart rate variability. Standards of measurement, physiological interpretation, and clinical use. Circulation. 1996;93:1043-1065.[PubMed]
  • Trejo LJ, Kochavi R, Kubitz K, Montgomery LD, Rosipal R, Matthews B. EEG-based estimation of cognitive fatigue. In: Caldwell JA, Wesensten NJ, editors. Proceedings of SPIE Vol. 5797: Bio-monitoring for Physiological and Cognitive Performance During Military Operations. Orlando, FL: SPIE Defense & Security Symposium; 2005. p. 105-115.
  • Waard D, Brookhuis KA. Assessing driver status: a demonstration experiment on the road. Accid Anal Prev. 1991;23(4):297-307.[PubMed][Crossref]
  • Zhang L, Zhou WD, Jiao LC. Wavelet Support Vector Machine. IEEE Trans Syst Man Cybern B. 2004;34(1):34-39.[Crossref]
Document Type
Publication order reference
Identifiers
YADDA identifier
bwmeta1.element.-psjd-doi-10_2478_v10013-010-0007-7
JavaScript is turned off in your web browser. Turn it on to take full advantage of this site, then refresh the page.