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.
Decoding eeg rhythms during action observation, motor imagery, and execution for standing and sitting.IEEE sensors journal, 20(22):13776–13786, 2020
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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.