Improving Cognitive Workload Prediction from fNIRS Data through Class-Aware and Block-Aware Domain Adaptation

The proposed class-aware and block-aware domain adaptation (CABA-DA) method can effectively minimize the intra-class domain discrepancy and maximize the inter-class domain discrepancy, leading to improved cognitive workload classification performance from fNIRS data across different subjects and sessions.