Abstract
BackgroundNear-infrared spectroscopy (NIRS) is an optical imaging technology that has recently been investigated for use in a safe, non-invasive brain-computer interface (BCI) for individuals with severe motor impairments. To date, most NIRS-BCI studies have attempted to discriminate two mental states (e.g., a mental task and rest), which could potentially lead to a two-choice BCI system. In this study, we attempted to automatically differentiate three mental states - specifically, intentional activity due to 1) a mental arithmetic (MA) task and 2) a mental singing (MS) task, and 3) an unconstrained, "no-control (NC)" state - to investigate the feasibility of a three-choice system-paced NIRS-BCI.ResultsDeploying a dual-wavelength frequency domain near-infrared spectrometer, we interrogated nine sites around the frontopolar locations while 7 able-bodied adults performed mental arithmetic and mental singing to answer multiple-choice questions within a system-paced paradigm. With a linear classifier trained on a ten-dimensional feature set, an overall classification accuracy of 56.2% was achieved for the MA vs. MS vs. NC classification problem and all individual participant accuracies significantly exceeded chance (i.e., 33%). However, as anticipated based on results of previous work, the three-class discrimination was unsuccessful for three participants due to the ineffectiveness of the mental singing task. Excluding these three participants increases the accuracy rate to 62.5%. Even without training, three of the remaining four participants achieved accuracies approaching 70%, the value often cited as being necessary for effective BCI communication.ConclusionsThese results are encouraging and demonstrate the potential of a three-state system-paced NIRS-BCI with two intentional control states corresponding to mental arithmetic and mental singing.
Highlights
Near-infrared spectroscopy (NIRS) is an optical imaging technology that has recently been investigated for use in a safe, non-invasive brain-computer interface (BCI) for individuals with severe motor impairments
We investigated the feasibility of a system-paced NIRS-Brain-computer interface (BCI) with one IC state corresponding to the performance of either mental arithmetic (MA) or mental singing (MS) [14]
An linear discriminant analysis (LDA) classifier trained on a 10-dimensional feature set allowed for the most accurate classification of MA
Summary
Near-infrared spectroscopy (NIRS) is an optical imaging technology that has recently been investigated for use in a safe, non-invasive brain-computer interface (BCI) for individuals with severe motor impairments. Many individuals with severe and multiple motor disabilities cannot communicate through the conventional avenues of speech and gesture. Many such individuals may lack sufficient motor control to operate common movement-based access devices (e.g.,mechanical switches, eye-trackers) [1]. Near-infrared spectroscopy (NIRS) is an optical imaging technology that has been recently investigated as a safe, non-invasive brain response measurement technology for potential use in BCI applications [3,4,5,6]. Note that NIRS optode placement in areas covered by hair is much more difficult, and may take considerably longer to achieve adequate signalto-noise ratio
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