Multimodal Pain Classification (m-PainAttnNet)
Extended PainAttnNet with attention-based fusion of ECG, EMG, and EDA signals, achieving 98.8% accuracy on 5-class pain intensity classification from the BioVid dataset.
Extended PainAttnNet with attention-based fusion of ECG, EMG, and EDA signals, achieving 98.8% accuracy on 5-class pain intensity classification from the BioVid dataset.