EMG-Finger-Kinematics (EMG-FK) dataset
Authors/Creators
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1.
Université Libre de Bruxelles
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2.
Fund for Scientific Research
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3.
University of Mons
Description
This dataset contains EMG and kinematic data from 20 participants.
EMG: 8 channels acquired at 500 Hz around the forearm using MindRove sensors (EMG armband | muscle sensor).
Kinematics: 15 joint angles (in degrees) acquired using MediaPipe hand tracking and linearly interpolated to 500 Hz.
Each participant performed 30 minutes of free, unconstrained finger gestures while keeping the hand position fixed.
The files can be easily loaded using the MNE Python package. No preprocessing has been applied to the dataset. Exact synchronization is guaranteed between EMG channels and within kinematic channels. However, a constant shift of approximately 300 ms can be observed between the two signal types.
The source code of the data acquisition framework and the benchmark evaluation is available on GitHub at GitHub/TRR_EMG-FK
A video demonstration of the data acquisition procedure, with training and testing of a machine learning model for hand gesture recognition, is available on YouTube at https://youtu.be/fDK7dXqEAEI
Files
Files
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