• Acta Optica Sinica
  • Vol. 36, Issue 5, 517001 (2016)
Jiang Jin*, Jiao Xuejun, Pan Jinjin, Wang Chunhui, Zhang Zhen, Cao Yong, Yang Hanjun, and Xu Fenggang
Author Affiliations
  • [in Chinese]
  • show less
    DOI: 10.3788/aos201636.0517001 Cite this Article Set citation alerts
    Jiang Jin, Jiao Xuejun, Pan Jinjin, Wang Chunhui, Zhang Zhen, Cao Yong, Yang Hanjun, Xu Fenggang. Assessment of Mental Workload Influenced by Different Emotional State Using fNIRS[J]. Acta Optica Sinica, 2016, 36(5): 517001 Copy Citation Text show less
    References

    [1] Hoc J M. From human-machine interaction to human-machine cooperation[J]. Ergonomics, 2000, 43(7): 833-843.

    [2] Zhang J H, Peng X D, Hua L, et al.. Classifying human operator functional state based on electrophysiological and performance measures and fuzzy clustering method[J]. Cognitive Neurodynamics, 2013, 7(6): 477-494.

    [3] Parasuraman R, Cosenzo K A, Visser E D. Adaptive automation for human supervision of multiple uninhabited vehicles: Effects on change detection, situation awareness and mental workload[J]. Journal of Environmental Science & Health Part A, 2010, 38(2): 289-299.

    [4] Wilson G F, Russell C A, Davis I. The importance of determining individual operator capabilities when applying adaptive aiding[C]. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 2006: 141-145.

    [5] Borghini G, Astolfi L, Vecchiato G, et al.. Measuring neurophysiological signals in aircraft pilots and car drivers for the assessment of mental workload, fatigue and drowsiness [J]. Neuroscience & Biobehavioral Reviews, 2014, 44: 58-75.

    [6] Qin G, Yang W, Fei S, et al.. Mental workload measurement for emergency operating procedures in digital nuclear power plants [J]. Ergonomics, 2013, 56(7): 1070-1085.

    [7] Wang Raofen. Fuzzy modeling method′s research of operator functional state[D]. Shanghai: East China University of Science and Technology,2012: 3-5.

    [8] Yang S, Zhang J. An adaptive human-machine control system based on multiple fuzzy predictive models of operator functional state[J]. Biomedical Signal Processing & Control, 2013, 8(3): 302-310.

    [9] Fallahi M, Motamedzade M, Heidarimoghadam R, et al.. Effects of mental workload on physiological and subjective responses during traffic density monitoring: A field study[J]. Applied Ergonomics, 2016, 52: 95-103.

    [10] Kopf J, Dresler T, Reicherts P, et al.. Effect of emotional content on brain activation and the late positive potential in a word n-back task[J]. PLoS ONE, 2013, 8(9): e75598.

    [11] Townsend J D, Sugar C A, Walshaw P D, et al.. Front striatal neuroimaging findings differ in patients with bipolar disorder who have or do not have ADHD comorbidity[J]. Journal of Affective Disorders, 2013, 147(1-3): 389-396.

    [12] Yang Shaozeng. Prediction and regulation of operator functional state based on multiple physiological data and fuzzy modeling methods[D]. Shanghai: East China University of Science and Technology, 2014: 7-16.

    [13] Ayaz H, Shewokis P A, Bunce S, et al.. Optical brain monitoring for operator training and mental workload assessment [J]. NeuroImage, 2012, 59(1): 36-47.

    [14] Pan Jinjin, Jiao Xuejun, Jiang Jin, et al.. Mental workload assessment based on functional near-infrared spectroscopy[J]. Acta Optica Sinica, 2014, 34(11): 1130002.

    [15] Pan Jinjin, Jiao Xuejun, Jiao Dian, et al.. Study on variation in cortex oxygen with task features using functional near-infrared spectroscopy[J]. Acta Optica Sinica, 2015, 35(8): 0817001.

    [16] Izzetoglu K, Ayaz H, Hing J T, et al.. UAV operators workload assessment by optical brain imaging technology (fNIR)[M]. //Handbook of unmanned aerial vehicles. New York: Springer, 2015: 2475-2500

    [17] Zhang Yong, Chen Bin, Li Dong. A three-dimensional geometric Monte Carlo method for simulation of light propagation in biological tissues[J]. Chinese J Lasers, 2015, 42(1): 0104003.

    [18] Xiong Yang, Si Minzhen, Gao Fei, et al.. Study on cervical cancer oxyhemoglobin using near-infrared surface-enhanced Raman spectroscopy[J]. Chinese J Lasers, 2015, 42(1): 0115001.

    [19] Chiarelli A M, Maclin E L, Fabiani M, et al.. A kurtosis-based wavelet algorithm for motion artifact correction of fNIRS data[J]. NeuroImage, 2015, 112: 128-137.

    [20] Wu Chunyang, Lu Qipeng, Ding Haiquan, et al.. Near-infrared non-invasive blood glucose measurement using human tissue fluid[J]. Acta Optica Sinica, 2013, 33(11): 1117001.

    [21] Zhou Zhenyu, Yang Hongyu, Gong Hui, et al.. Brain signal analysis of functional near-infrared imaging based on Hilbert-Huang transform[J]. Acta Optica Sinica, 2007, 27(2): 307-312.

    [22] Piper S K, Krueger A, Koch S P, et al.. A wearable multi-channel fNIRS system for brain imaging in freely moving subjects [J]. NeuroImage, 2014, 85(2): 64-67.

    [23] Hall M, Chaudhary U, Rey G, et al.. Fronto-temporal mapping and connectivity using NIRS for language-related paradigms[J]. Journal of Neurolinguistics, 2013, 26(1): 178-194.

    [24] Doi H, Nishitani S, Shinohara K. NIRS as a tool for assaying emotional function in the prefrontal cortex[J]. Frontiers in Human Neuroscience, 2013, 7(1): 56-67.

    [25] Ozawa S, Matsuda G, Hiraki K. Negative emotion modulates prefrontal cortex activity during a working memory task: A NIRS study[J]. Frontiers in Human Neuroscience, 2014, 8(2): 46.

    [26] Fishburn F A, Norr M E, Medvedev A V, et al.. Sensitivity of fNIRS to cognitive state and load[J]. Frontiers in Human Neuroscience, 2014, 8(2): 76.

    [27] Lobacheva E M, Galatenko Y N, Gabidullina R F, et al.. Automated real-time classification of functional states based on physiological parameters[J]. Procedia-Social and Behavioral Sciences, 2013, 86: 373-378.

    [28] Wilson G F, Russell C A. Real-time assessment of mental workload using psychophysiological measures and artificial neural networks[J]. Journal of the Human Factors & Ergonomics Society, 2003, 45(4): 635-643.

    [29] Zhong Y, Zhang J. Operator functional state classification using least-square support vector machine based on recursive feature elimination technique[J]. Computer Methods & Programs in Biomedicine, 2014, 113(1): 101-115.

    [30] Ting C H, Mahfouf M, Nassef A, et al.. Real-time adaptive automation system based on identification of operator functional state in simulated process control operations[J]. IEEE Transactions on Systems Man & Cybernetics Part A, 2010, 40(2): 251-262.

    [31] Kirilina E, Jelzow A, Heine A, et al.. The physiological origin of task-evoked systemic artefacts in functional near infrared spectroscopy[J]. NeuroImage, 2012, 61(1): 70-81.

    [32] Xu C, Bray S, Reiss A L. Functional near infrared spectroscopy (NIRS) signal improvement based on negative correlation between oxygenated and deoxygenated hemoglobin dynamics[J]. NeuroImage, 2010, 49(4): 3039-3046.

    [33] Haeussinger F B, Sler T, Heinzel S, et al.. Reconstructing functional near-infrared spectroscopy (fNIRS) signals impaired by extra-cranial confounds: An easy-to-use filter method[J]. NeuroImage, 2014, 95(8): 69-79.

    [34] Peng Mingjin, Li Zhi. Analysis and feature extraction of laser micro-Doppler signatures based on Hilbert-Huang transforms [J]. Chinese J Lasers, 2013, 40(8): 0809004.

    [35] Xu Lu. A study on feature selection algorithm based on SVM-RFE and particle swarm optimization[D]. Changsha: Hunan Normal University, 2014: 63-75.

    [36] Durantin G, Gagnon J F, Tremblay S, et al.. Using near infrared spectroscopy and heart rate variability to detect mental overload[J]. Behavioural Brain Research, 2014, 259(2): 16-23.

    [37] Hu T Y, Xie X, Li J. Negative or positive The effect of emotion and mood on risky driving[J]. Transportation Research Part F, 2013, 16: 29-40.

    Jiang Jin, Jiao Xuejun, Pan Jinjin, Wang Chunhui, Zhang Zhen, Cao Yong, Yang Hanjun, Xu Fenggang. Assessment of Mental Workload Influenced by Different Emotional State Using fNIRS[J]. Acta Optica Sinica, 2016, 36(5): 517001
    Download Citation