Near infrared spectroscopy (NIRS) is a recently developed technique that can reveal hemodynamic and metabolic changes during cortical activation. Unlike established techniques, such as electroencephalography (EEG), functional magnetic resonance imaging (fMRI), and magnetoencephalography (MEG), NIRS could be more practical and user-friendly. NIRS has been used to study hemodynamic responses (changes of oxy- and deoxyhemoglobin) to cognitive, visual, and motor tasks. A big challenge when using NIRS is the classification of single trial data. Single trial classification requires improving the signal to noise ratio (SNR) and reducing false classifications that primarily stem from misclassification of physiological noise. To determine whether the recorded signal reflects local cortical activation or a global response of the cardiovascular system, it is essential to identify systemic influences.
The goal of this project is to investigate the influence of systemic parameters on hemodynamic responses measured with NIRS. Another aim is to design appropriate signal processing approaches to reduce the systemic influences in the recorded NIRS signals.