 Aim: To address the domain shift in fNIRS data across sessions and subjects for task label alignment, we exploited two domain adaptation approaches - Gromov-Wasserstein (G-W) and Fused Gromov-Wasserstein (FG-W)  . Approach:  We applied G-W for session-by-session alignment and FG-W for subject-by-subject alignment with Hellinger distance as underlying metric to fNIRS data acquired during different n-back task levels.
<clarity>  Aim: To address the domain shift in fNIRS data across sessions and subjects for task label alignment, we exploited two domain adaptation approaches - Gromov-Wasserstein (G-W) and Fused Gromov-Wasserstein (FG-W)  . Approach:  We applied G-W for session-by-session alignment and FG-W for subject-by-subject alignment with Hellinger distance as underlying metric to fNIRS data acquired during different n-back task levels.
 Aim: To address the domain shift in fNIRS data across sessions and subjects . In order to address this problem, two domain adaptation approaches - Gromov-Wasserstein (G-W) and Fused Gromov-Wasserstein (FG-W) . Approach: We applied G-W for session-by-session alignment and FG-W for subject-by-subject alignment with Hellinger distance as underlying metric to fNIRS data acquired during different n-back task levels.