GREF Dataset: On the benefit of FMG and EMG sensor fusion for gesture recognition using cross-subject validation
Date
2024Author
Description
The Gesture Recognition using EMG and FMG TU Darmstadt (GREFTUD) dataset contains labeled recordings of electromyography (EMG) and forcemyography recordings of 13 healthy subjects, each of whom performed 66 distinct hand movements.
The movements were labeled using a high speed camera and the start and end time (in ms) of each movement were noted manually. The dataset was presented in our paper "On the Benefit of FMG and EMG Sensor Fusion for Gesture Recognition Using Cross-Subject Validation".
The file "dataset.hdf5" contains the complete dataset, including the manual labels, but no video data.
An example on how to use the dataset can be found in "hdf5_example.ipynb".
Subject
Electromyography (EMG);Ferroelectrets;Force myography (FMG);Gesture recognition;Sensor fusionDFG subject classification
4.41-06 Biomedizinische SystemtechnikURI
https://tudatalib.ulb.tu-darmstadt.de/handle/tudatalib/4528https://doi.org/10.48328/tudatalib-1707
Related third party funded projects
DFG | GRK2761 | TP_Kupnik_GRK_2761Related Resources
- References: DOI:https://doi.org/10.1109/TNSRE.2025.3543649
Collections
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Sensor Fusion [1]
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Except where otherwise noted, this item's license is described as Creative Commons Attribution 4.0