Monitoring Mental Fatigue in Analog Space Environment Using Optical Brain Imaging
Affiliation(s)
Tsinghua University, Beijing, China;National Laboratory of Human Factors Engineering, China Astronaut Research and Training Centre, Beijing, China. Tsinghua University, Beijing, China.
Tsinghua University, Beijing, China;National Laboratory of Human Factors Engineering, China Astronaut Research and Training Centre, Beijing, China. Tsinghua University, Beijing, China.
ABSTRACT
Accurate assessment of mental fatigue level would improve operational safety and efficacy of astronauts for long-term space flight. Identification of neurophysiological markers can index impending overload or fatigue before performance decrements using neuroimaging technologies. The current study utilized functional near-infrared spectroscopy (fNIR) to investigate the relationship of hemodynamic response in prefrontal cortex with changes of mental fatigue level, task performance (reaction time) during n-back working memory task and routine work task in analog space environment. Results indicated that the information entropy of hemodynamic response is related to task performance and subjective self-reported measures; the reaction time is predicted by regression analysis; and the accuracy of mental fatigue classification approaches 90%. Since fNIR is a portable, wearable and minimally intrusive methodology, it has the potential to be deployed in future space environments to monitoring mental fatigue and assessing the effort of operators in field environments.
Accurate assessment of mental fatigue level would improve operational safety and efficacy of astronauts for long-term space flight. Identification of neurophysiological markers can index impending overload or fatigue before performance decrements using neuroimaging technologies. The current study utilized functional near-infrared spectroscopy (fNIR) to investigate the relationship of hemodynamic response in prefrontal cortex with changes of mental fatigue level, task performance (reaction time) during n-back working memory task and routine work task in analog space environment. Results indicated that the information entropy of hemodynamic response is related to task performance and subjective self-reported measures; the reaction time is predicted by regression analysis; and the accuracy of mental fatigue classification approaches 90%. Since fNIR is a portable, wearable and minimally intrusive methodology, it has the potential to be deployed in future space environments to monitoring mental fatigue and assessing the effort of operators in field environments.
Cite this paper
X. J. Jiao, J. Bai, S. G. Chen and Q. J. Li, "Monitoring Mental Fatigue in Analog Space Environment Using Optical Brain Imaging," Engineering, Vol. 5 No. 5B, 2013, pp. 53-57. doi: 10.4236/eng.2013.55B011.
X. J. Jiao, J. Bai, S. G. Chen and Q. J. Li, "Monitoring Mental Fatigue in Analog Space Environment Using Optical Brain Imaging," Engineering, Vol. 5 No. 5B, 2013, pp. 53-57. doi: 10.4236/eng.2013.55B011.
References
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[1] Van Beekvelt, M. C. Colier, W. N. Wevers, R. A. Van and B. G. Engelen, “Performance of Near-Infrared Spectroscopy in Measuring Local O2 Consumption and Blood Flow in Skeletal Muscle,” Journal of Applied Physiology, Vol. 90, No. 2, 2001, pp.511-519. [2] A. Villringer and B. Chance, “Non-Invasive Optical Spectroscopy and Imaging of Human Brain Function,” Trends in Neuroscience, Vol. 20, No. 10, 1997, pp. 435-442. doi:10.1016/S0166-2236(97)01132-6 [3] Hasan Ayaza, P. A. Shewokis et al., “Optical Brain Monitoring for Operator Training and Mental Workload Assessment,” NeuroImage, Vol. 59, 2012, pp. 36-47. doi:10.1016/j.neuroimage.2011.06.023 [4] C. Zhang, C. X. Zheng, X. L. Yu and Y. Ouyang, “Estimating VDT Mental Fatigue Using Multichannel Linear Descriptors and KPCA-HMM,” EURASIP Journal on Advances in Signal Processing, Vol. 2008, No. 1, pp.185638. [5] J. Wu and D. T. Ye. “Evaluation of Anti-Fatigue Effect of Health Protection Food with fNIR,” Spectroscopy and Spectral Analysis, Vol. 29, No. 9, pp. 2357-2360. [6] Y. Son and B. Yazlcl, “Near Infrared Imaging and Spectroscopy for Brain Activity Monitoring,” Advances in Sensing with Security Applications, Vol. 2, 2006, pp 341-372. doi:10.1007/1-4020-4295-7_15 [7] Ajit. Devaraj, “Signal Processing for Functional Near-Infrared Neuroimaging,” Drexel Theses and Dissertations, 2005. [8] Ramnani, N. and Owen, A.M. “Anterior Prefrontal Cortex: Insights into Function from Anatomy and Neuroimaging,” Nat Rev Neurosci, Vol. 5, No. 3, 2004, pp. 184-194. doi:10.1038/nrn1343