• Journal of Innovative Optical Health Sciences
  • Vol. 10, Issue 3, 1750006 (2017)
Xiaolong Liu1 and Keum-Shik Hong2、3、*
Author Affiliations
  • 1School of Mechanical Engineering, Pusan National University, 2 Busandaehak-ro, Geumjeong-gu, Busan 46241, Republic of Korea
  • 2School of Mechanical Engineering and Department of Cogno-Mechatronics Engineering, Pusan National University
  • 32 Busandaehak-ro, Geumjeong-gu, Busan 46241, Republic of Korea
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    DOI: 10.1142/s1793545817500067 Cite this Article
    Xiaolong Liu, Keum-Shik Hong. Detection of primary RGB colors projected on a screen using fNIRS[J]. Journal of Innovative Optical Health Sciences, 2017, 10(3): 1750006 Copy Citation Text show less

    Abstract

    In this study, functional near-infrared spectroscopy (fNIRS) is utilized to measure the hemodynamic responses (HRs) in the visual cortex of 14 subjects (aged 22–34 years) viewing the primary red, green, and blue (RGB) colors displayed on a white screen by a beam projector. The spatiotemporal characteristics of their oxygenated and deoxygenated hemoglobins (HbO and HbR) in the visual cortex are measured using a 15-source and 15-detector optode configuration. To see whether the activation maps upon RGB-color stimuli can be distinguished or not, the t-values of individual channels are averaged over 14 subjects. To find the best combination of two features for classification, the HRs of activated channels are averaged over nine trials. The HbO mean, peak, slope, skewness and kurtosis values during 2–7 s window for a given 10 s stimulation period are analyzed. Finally, the linear discriminant analysis (LDA) for classifying three classes is applied. Individually, the best classification accuracy obtained with slope-skewness features was 74.07% (Subject 1), whereas the best overall over 14 subjects was 55.29% with peak-skewness combination. Noting that the chance level of 3-class classification is 33.33%, it can be said that RGB colors can be distinguished. The overall results reveal that fNIRS can be used for monitoring purposes of the HR patterns in the human visual cortex.
    Xiaolong Liu, Keum-Shik Hong. Detection of primary RGB colors projected on a screen using fNIRS[J]. Journal of Innovative Optical Health Sciences, 2017, 10(3): 1750006
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