"Elbow joint angle and sEMG"

"We release a dataset for upper-limb motion analysis and rehabilitation-oriented human\u2013machine interaction, consisting of multi-channel surface electromyography (sEMG) signals and corresponding elbow flexion\u2013extension joint angle trajectories. The dataset covers repeated elbow flexion\u2013extension movements, and the sEMG signals and joint angles need to be temporally aligned before use. It supports research on continuous joint angle estimation, motion intention decoding, cross-subject generalization, and few-shot transfer learning, and can be used to train and evaluate control algorithms for rehabilitation robots and exoskeleton systems."