MECASA, an additive self-attention architecture built on CAS-ViT, reports peak accuracies of 75.07% (EEG), 86.52% (fNIRS), and 87.34% (fused) on the SMR Hybrid BCI dataset.
Exploring the role of primary and supplementary motor areas in simple motor tasks with fnirs
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.HC 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
MECASA: Motor Execution Classification using Additive Self-Attention for Hybrid EEG-fNIRS Data
MECASA, an additive self-attention architecture built on CAS-ViT, reports peak accuracies of 75.07% (EEG), 86.52% (fNIRS), and 87.34% (fused) on the SMR Hybrid BCI dataset.