Real-time assessment of mental workload with near-infrared spectroscopy: Potential for human-computer interaction. - Fantini, Sergio (Professor of Biomedical Engineering); Sassaroli, Angelo.; Tong, Yunjie.; Hirshfield, Leanne M.; Girouard, Audrey.; Solovey, Erin Treacy.; Jacob, Robert J. K. (Tufts University. Tisch Library., 2017)
Human computer interaction (HCI) is an interdisciplinary field that involves the study and development of user interfaces for computers. One challenge of HCI is the collection of quantitative information on human computer users, which is fundamental for evaluation purposes and real-time input. The collection of neurophysiological data of cognitive workload has been proposed using multivariate electroencephalography (EEG) and also functional near infrared spectroscopy (fNIRS) In this work we propose to use machine learning algorithms for the analysis of near-infrared data, and apply this approach to process data collected on the forehead of human subjects while they perform tasks of increasing cognitive workload levels. The purpose is to develop a tool for quantitative and real-time assessment of cognitive workload to provide continuous feedback to a dynamic human-computer interface.