EMG from forearm datasets for hand gestures recognition
- 1. Institute of Neuroinformatics, UZH/ETH Zurich
This dataset contains 2 sets of sEMG recordings: a set containing PINCH movements (4 pinches between thumb and index/middle/ring/pinky finger) and a set containing ROSHAMBO 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 PINCH set contains recordings of 22 subjects whilst the ROSHAMBO 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 ROSHAMBO set can be found in:
Donati, Elisa, et al. "Processing EMG signals using reservoir computing on an event-based neuromorphic system." 2018 IEEE Biomedical Circuits and Systems Conference (BioCAS). IEEE, 2018.
For each session, the dataset contains 2 *.npy files one specifying the EMG data (*_emg.npy) the other one (*_ann.npy) specifying the corresponding gestures along the sampled EMG. The data can be easily loaded in python with numpy.