Multi-Modal Dataset for "Towards Robust Surface Electromyography for Upper Limb Protheses using Machine Learning "

The dataset contains sEMG recordings from 10 anatomically intact participants. The data is separated into 13 trials, 11 of which were performed under manual intervention to vary one of the following parameters: Skin Temperature, Arm Position, Electrode Position, Impedance. Within each trial the participants perform 2 repetitions of 6 different hand grasps, held for 5 seconds.
The data was recorded using custom-built sEMG sensors that also permitted the recording of skin temperature and skin-electrode impedance. Recordings of these features are provided with the data, recorded following the completion of a grasp.

The data were recorded following approval granted by the University of Bath Research Ethics Approval Committee for Health, study ID: EP 23 019.