Application of near-infrared spectroscopy for discrimination of mental workloads

A. Sassaroli; F. Zheng; M. Coutts; L. H. Hirshfield; A. Girouard; E. T. Solovey; R. J.K. Jacob; Y. Tong; B. De; S. Fantini

doi:10.1117/12.807737

Application of near-infrared spectroscopy for discrimination of mental workloads

A. Sassaroli, F. Zheng, M. Coutts, L. H. Hirshfield, A. Girouard, E. T. Solovey, R. J.K. Jacob, Y. Tong, B. De, S. Fantini

Research output: Contribution to journal › Conference Article › peer-review

3 Scopus citations

Abstract

We show the potential of functional near-infrared spectroscopy for the discrimination of mental workloads during a cognitive task with two different levels of difficulty. Standard data analysis based on filtering and folding average procedures were carried out to locate those source-detector pairs sensitive to the activated cortical regions. On these channels we applied two classification algorithms for the discrimination of mental workloads. Both algorithms showed a high percentage of successful classifications (>80%) on three over a total of four subjects where brain activation was detected. These results are comparable to standard scores found in the field of electroencephalography.

Original language	English (US)
Article number	71741H
Journal	Progress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume	7174
DOIs	https://doi.org/10.1117/12.807737
State	Published - 2009
Externally published	Yes
Event	Optical Tomography and Spectroscopy of Tissue VIII - San Jose, CA, United States Duration: Jan 25 2009 → Jan 27 2009

Keywords

Brain imaging
Functional near-infrared spectroscopy
Human computer interaction
Mental workload

ASJC Scopus subject areas

Electronic, Optical and Magnetic Materials
Atomic and Molecular Physics, and Optics
Biomaterials
Radiology Nuclear Medicine and imaging

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10.1117/12.807737

Cite this

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title = "Application of near-infrared spectroscopy for discrimination of mental workloads",

abstract = "We show the potential of functional near-infrared spectroscopy for the discrimination of mental workloads during a cognitive task with two different levels of difficulty. Standard data analysis based on filtering and folding average procedures were carried out to locate those source-detector pairs sensitive to the activated cortical regions. On these channels we applied two classification algorithms for the discrimination of mental workloads. Both algorithms showed a high percentage of successful classifications (>80%) on three over a total of four subjects where brain activation was detected. These results are comparable to standard scores found in the field of electroencephalography.",

keywords = "Brain imaging, Functional near-infrared spectroscopy, Human computer interaction, Mental workload",

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journal = "Progress in Biomedical Optics and Imaging - Proceedings of SPIE",

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TY - JOUR

T1 - Application of near-infrared spectroscopy for discrimination of mental workloads

AU - Sassaroli, A.

AU - Zheng, F.

AU - Coutts, M.

AU - Hirshfield, L. H.

AU - Girouard, A.

AU - Solovey, E. T.

AU - Jacob, R. J.K.

AU - Tong, Y.

AU - De, B.

AU - Fantini, S.

PY - 2009

Y1 - 2009

N2 - We show the potential of functional near-infrared spectroscopy for the discrimination of mental workloads during a cognitive task with two different levels of difficulty. Standard data analysis based on filtering and folding average procedures were carried out to locate those source-detector pairs sensitive to the activated cortical regions. On these channels we applied two classification algorithms for the discrimination of mental workloads. Both algorithms showed a high percentage of successful classifications (>80%) on three over a total of four subjects where brain activation was detected. These results are comparable to standard scores found in the field of electroencephalography.

AB - We show the potential of functional near-infrared spectroscopy for the discrimination of mental workloads during a cognitive task with two different levels of difficulty. Standard data analysis based on filtering and folding average procedures were carried out to locate those source-detector pairs sensitive to the activated cortical regions. On these channels we applied two classification algorithms for the discrimination of mental workloads. Both algorithms showed a high percentage of successful classifications (>80%) on three over a total of four subjects where brain activation was detected. These results are comparable to standard scores found in the field of electroencephalography.

KW - Brain imaging

KW - Functional near-infrared spectroscopy

KW - Human computer interaction

KW - Mental workload

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VL - 7174

JO - Progress in Biomedical Optics and Imaging - Proceedings of SPIE

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ER -

Application of near-infrared spectroscopy for discrimination of mental workloads

Abstract

Keywords

ASJC Scopus subject areas

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