Cross-subject classification of speaking modes using fNIRS
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part II
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Near-infrared spectroscopy (NIRS) enables non-invasive recording of cortical hemoglobin oxygenation in human subjects through the intact skull using light in the near-infrared range to determine. Recently, NIRS-based brain-computer interfaces are introduced for discriminating left and right-hand motor imagery. A neuroimaging study has also revealed event-related hemodynamic responses associated with the performance of mental arithmetic tasks. This paper proposes a novel BCI for detecting changes resulting from increases in the magnitude of operands used in a mental arithmetic task, using data from single-trial NIRS brain signals. We measured hemoglobin responses from 20 healthy subjects as they solved mental arithmetic problems with three difficulty levels. Accuracy in recognizing one difficulty level from another is then presented using 5麓5-fold cross-validations on the data collected. The results yielded an overall average accuracy of 71.2%, thus demonstrating potential in the proposed NIRS-based BCI in recognizing difficulty of problems encountered by mental arithmetic problem solvers.