Mental iş yükü ve uyanık olma durumunda kullanılan nöroergonomik yöntemler

Year 2018, Volume: 43 Number: Supplement 1, 295 - 300, 29.12.2018

Gizem Gül Koç Ali Kokangül

https://doi.org/10.17826/cumj.448430

Abstract

Nöroergonomi, insan beyninin iş
performansı ve günlük yaşam sırasında karşılaşılan beyin fonksiyonu ve
davranışları hakkında değerli bilgiler elde edebilme adına geliştirilen bir bilim
dalıdır. Teori ve prensiplerini ergonomi, sinirbilim ve insan faktörlerinden
alır. Nöroergonomi çalışmaları sırasında beyin yapılarını, mekanizmalarını ve
işlevlerini anlamak için nörogörüntüleme teknikleri kullanılır. Nörogörüntüleme
teknikleri, iki genel kategoriye ayrılır; bunlar, elektroensefalografi gibi (EEG) gibi uyaranlara cevapta nöronal
aktivitenin direkt göstergeleri ve pozitron emisyon tomografisi - bilgisayarlı
tomografi (PET-BT), fonksiyonel manyetik rezonans görüntüleme (fMRG), fonksiyonel yakın kızılötesi spektroskopi
(fNIRS), fonksiyonel Transkranyal Doppler (fTCD) gibi nöronal
aktivitenin endirekt metabolik göstergeleridir. Bu derlemede mental iş yükü ve
uyanık olma durumunda kullanılan nöroergonomik yöntemler gözden geçirilmiştir.

Keywords

Nörobilim, ergonomi

Neuroergonomic methods used in mental workload and vigilance

Abstract

Neuroergonomics is the study of the behavior of the human brain. Its theories and principles are based on ergonomics, neuroscience, and the extant literature on human beings. Neuroimaging studies use neuroimaging techniques to understand the structures, mechanisms, and functions of the brain. Neuroimaging techniques are divided into two general categories: direct displays of neuronal activity in response to stimuli, such as electroencephalography (EEG) and positron emission tomography-computed tomography (PET-CT), and indirect metabolic indicators of neuronal activity, such as functional magnetic resonance imaging (fMRG), functional near-infrared spectroscopy (fNIRS), and functional transcranial Doppler sonography (fTCD). This review outlines the techniques and current applications of neuroergonomic methods used in mental workload and vigilance.

References

• 1. Parasuraman R., Rizzo M. Neuroergonomics: The brain at work. New York, NY: Oxford University Press. 2008.
• 2. Parasuraman R., Wilson G.F. Putting the brain to work: Neuroergonomics past, present and future. Human Factors, 2008, 50: 468–474.
• 3. Lees MN., Cosman JD., Lee JD., Fricke N., Rizzo M. Translating cognitive neuroscience to the driver's operational environment: a neuroergonomic approach. The American Journal of Psychology (AJP), 2010, 123:391-411.
• 4. Bandettini PA., Wong EC., Hinks RS, Tikofsky RS., Hyde JS. Time course EPI of human brain function during task activation. Magnetic Resonance in Medicine, 1992;25:390-97.
• 5. Kwong KK., Belliveau JW., Chesler DA., Goldberg IE., Weisskoff RM., Poncelet BP., Kennedy DN., Hoppel BE., Cohen MS., Turner R., et al. Dynamic magnetic resonance imaging of human brain activity during primary sensory stimulation. Proceedings of the National Academy of Sciences USA, 1992;89:5675-79.
• 6. Ogawa S., Lee TM., Kay AR., Tank DW. Brain magnetic resonance imaging with contrast dependent on blood oxygenation. Proceedings of the National Academy of Sciences USA, 1990, 87:9868-72.7. Wierenga CE., and Bondi MW. Use of Functional Magnetic Resonance Imaging in the Early Identification of Alzheimer’s Disease. Neuropsychol Rev. 2007, 17: 127–143.8. Kim DI., Sui J., Rachakonda S., White T., Manoach DS., Clark VP., Ho BC., Schulz SC., Calhoun VD. Identification of imaging biomarkers in schizophrenia: a coefficient-constrained independent component analysis of the mind multi-site schizophrenia study. Neuroinformatics,. 2010, 8:213-29.
• 9. Richards TL., Berninger VW. Abnormal fMRI Connectivity in Children with Dyslexia During a Phoneme Task: Before But Not After Treatment. The Journal of Neurolinguistics, 2008, 21:294-304.
• 10. Wise RG., Preston C. What is the value of human FMRI in CNS drug development? Drug Discovery Today, 2010,15:973-80.
• 11. Glover GH. Overview of Functional Magnetic Resonance Imaging. Neurosurgery Clinics of North America, 2011, 22: 133-139.
• 12. Buxton RB., Frank LR. A model for the coupling between cerebral blood flow and oxygen metabolism during neural stimulation. The Journal of Cerebral Blood Flow & Metabolism, 1997, 17:64-72.
• 13. Buxton RB., Wong EC., Frank LR. Dynamics of blood flow and oxygenation changes during brain activation: the balloon model. Magnetic Resonance in Medicine, 1998,39:855-64.
• 14. Davis TL., Kwong KK., Weisskoff RM., Rosen BR. Calibrated functional MRI: mapping the dynamics of oxidative metabolism. Proceedings of the National Academy of Sciences USA, 1998, 95:1834-9.
• 15. Lyman S., Ferguson SA., Braver ER., Williams AF. Older driver involvements in police reported crashes and fatal crashes: trends and projections. Injury Prevention, 2002, 8:116-20.
• 16. Preusser DF., Williams AF., Ferguson SA., Ulmer RG., Weinstein HB. Fatal crash risk for older drivers at intersections. Accident Analysis & Prevention,. 1998, 30:151-9.
• 17. Filley CM. Encephalopathies. In: Rizzo M, Eslinger PJ, editors. Principles and Practice of Behavioral Neurology and Neuropsychology. Philadelphia, PA: Saunders; 2004. pp. 635–653.
• 18. Dewar RE. Age differences - Drivers old and young. In: Dewar RE, Olson PL, editors. Human Factors in Traffic Safety. 2. Tucson, AZ: Laywers and Judges Publishing Company, Inc; 2007. pp. 143–158.
• 19. McGwin G Jr., Brown DB. Characteristics of traffic crashes among young, middle-aged, and older drivers. Accident Analysis & Prevention, 1999,31:181-98.
• 20. Lin X., Sai L., Yuan Z. Detecting Concealed Information with Fused Electroencephalo- graphy and Functional Near-infrared Spectroscopy. Neuroscience 2018 Jun, 10. pii: S0306-4522(18)30469-X. doi: 10.1016/j.neuroscience.2018.06.049.
• 21. Fischer BM., Siegel BA., Weber WA., von Bremen K., Beyer T., Kalemis A. PET/CT is a cost-effective tool against cancer: synergy supersedes singularity. the European Journal of Nuclear Medicine and Molecular Imaging, 2016,43:1749-52. 22. Zukotynski K., Kuo PH., Mikulis D., Rosa-Neto P., Strafella AP., Subramaniam RM., Black SE. PET/CT of Dementia. American Journal of Roentgenology (AJR), 2018,27:1-14.
• 23. Fischer BM., Siegel BA., Weber WA., von Bremen K., Beyer T., Kalemis A. PET/CT is a cost-effective tool against cancer: synergy supersedes singularity. European Journal of Nuclear Medicine and Molecular Imaging, 2016,43:1749-52.
• 24. Kutas M, McCarthy G, Donchin E. Augmenting mental chronometry: The P300 as a measure of stimulus evaluation time. Science 1977,197:792–95.
• 25. Carryl L., Baldwin CL., Coyne JT. Dissociable aspects of mental workload: Examinations of the P300 ERP component and performance assessments. Psychologia 2005,48: 102-119.
• 26. Luck S. Sources of dual-task interference: Evidence from human electrophysiology. Psychological Science 1998,9: 223–227.
• 27. Brookings JB., Wilson GF., Swain CR. Psychophysiological responses to changes in workload during simulated air traffic control. Biological Psychology 1996,42: 361–77.
• 28. Oliviera I., Grigori O., Guimaraes N. EEG Signal Analysis For Silent Visual Reading Classification. International Journal of Circuits, Systems And Signal Processing 2009,3:119-26.
• 29. Mostow J, Chang K-M, Nelson J. Toward Exploring EEG input in a Reading Tutor, AIED. LNCS, Springer, Heidelberg, 2011, 230-37.
• 30. Galan FC, Beal CR. “EEG Estimates of Engagement and Cognitive Workload Predict Math Problem Solving Outcomes”, User Modelling, Adaptation, and Personalization (UMAP), 2012, pp.51- 62.
• 31. Sakkalis V., Zervakis M., Micheloyannis S. Significant EEG features Involved in Mathematical Reasoning: Evidence from Wavelet Analysis. Brain Topography 2006,19:53-60.
• 32. Sharabaty H., Jammes, B., Esteve D., EEG analysis using HHT: One step toward automatic drowsiness scoring. 22nd International Conference on Advanced Information Networking and Applications – Workshops, 2008, 826-831.
• 33. Connolly JD., Goodale MA., Menon RS., Munoz DP. Human fMRI evidence for the neural correlates of preparatory set. Nature Neuroscience 2002,5:1345-52.
• 34. Duschek S, Hoffmann A, Montoro CI, Del Paso GAR, Schuepbach D, Ettinger U. Cerebral blood flow modulations during preparatory attention and proactive inhibition. Biol Psychol. 2018;18:30518. doi: 10.1016/j.biopsycho.2018.07.003.
• 35. Posner, MI, Petersen SE. The attention system of the human brain. Annual Review of Neuroscience 1990;13:25-42.