Long-Term Monitoring of NIRS and EEG Signals for Assessment of Daily Changes in Emotional Valence

Abstract

Mood disorders caused by chronic stress are mostly difficult to be recognized of by ourselves. Self-reported inventories, e.g., Beck Depression Inventory (BDI) and State-Trait Anxiety Inventory (STAI), as screening tests can elucidate the emotional valence; however, these tools are not designed for periodic monitoring in daily life. Moreover, positive affect is also hard to recognize without taking such self-reported inventories. Here we compared the indices of frontal alpha asymmetry (FAA) obtained from electroencephalography (EEG) data in the resting state and laterality index at rest (LIR) from near-infrared spectroscopy (NIRS) data. The Comfort Vector model (CVM) is another approach for using the feature value of prefrontal alpha wave fluctuation. In this paper, we discuss the applicability of these biomarkers for assessment of emotional valence. From experimental results from periodic NIRS and EEG recordings of two healthy subjects who participated for more than 4 weeks, feature values of FAA, LIR, and CVM were compared with BDI and STAI scores.