Application of near-infrared spectroscopy for discrimination of mental workloads. - Sassaroli, Angelo.; Zheng, Feng.; Girouard, Audrey.; Solovey, Erin Treacy.; Chauncey, Krysta.; Hirshfield, Leanne H.; Peck, Evan.; Jacob, Robert J. K.; Fantini, Sergio (Professor of Biomedical Engineering) (Tufts University. Tisch Library., 2017)
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. Copyright 2010 Society of Photo-Optical Instrumentation Engineers (SPIE) One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.