EMG from forearm datasets for hand gestures recognition

This dataset contains 2 sets of sEMG recordings: a set containing <strong>PINCH</strong> movements (4 pinches between thumb and index/middle/ring/pinky finger) and a set containing <strong>ROSHAMBO</strong> movements (3 movements: rock, paper, scissors). Both sets have been recorded with the Myo armband. The Myo is composed of 8 equally spaced non-invasive sEMG sensors that can be placed approximately around the middle of the forearm. The sampling frequency of Myo is 200 Hz. The output of the Myo is a.u.. The <strong>PINCH </strong>set contains recordings of 22 subjects whilst the <strong>ROSHAMBO</strong> set contains recordings of 10 subjects. Each subject performed 3 sessions, where each hand gesture was recorded 5 times, each lasting for 2s. Between the gestures a relaxing phase of 1s is present where the muscles could go to the rest position, removing any residual muscular activation. Full details for the <strong>ROSHAMBO</strong> set can be found in:

Donati, Elisa, et al. "Processing EMG signals using reservoir computing on an event-based neuromorphic system." <em>2018 IEEE Biomedical Circuits and Systems Conference (BioCAS)</em>. IEEE, 2018.

For each session, the dataset contains 2 <strong>*.npy</strong> files one specifying the EMG data (<strong>*_emg.npy</strong>) the other one (<strong>*_ann.npy</strong>) specifying the corresponding gestures along the sampled EMG. The data can be easily loaded in python with numpy.