MUnitQuest Familiarization Data for the Isometric Challenge

DOI

This dataset contains high-density surface electromyography (HDsEMG) recordings from the Isometric Challenge during the MUnitQuest Familiarization phase.

MUnitQuest is a community-driven competition on motor unit identification methods. The data and metadata of each recording follow the standardized EMG-BIDS format.

This dataset contains 100 HD-EMG recordings (experimental and simulated) across various isometric tasks with a tapozoidal or triangular effort profile. Each data file (.edf) is accompanied by the following metadata files specifying the recording set-up and the task: - electrodes.tsv: A tabular file specifying the electrode positions - coordsystem.json: The frame of reference of the electrode coordinates - channels.tsv: A tabular file providing a mapping from the electrode configuration to the data matrix - emg.json: Describing the recording hardware and configuration - events.tsv: A tabular file specifying the experimental protocol

Tutorials on how to import the EMG data provided in this dataset can be found in the MUnitQuest-Tutorial repository.

Identifier
DOI https://doi.org/10.18419/DARUS-6143
Metadata Access https://darus.uni-stuttgart.de/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.18419/DARUS-6143
Provenance
Creator Klotz, Thomas ORCID logo; Mamidanna, Pranav ORCID logo; Brandenburg, Paul; Enslin, Niklas; Rohlén, Robin ORCID logo; Raftery, William ORCID logo; Farina, Dario ORCID logo; Röhrle, Oliver ORCID logo
Publisher DaRUS
Contributor Klotz, Thomas; Utility IMSB
Publication Year 2026
Rights CC BY 4.0; info:eu-repo/semantics/openAccess; http://creativecommons.org/licenses/by/4.0
OpenAccess true
Contact Klotz, Thomas (University of Stuttgart); Utility IMSB (University of Stuttgart)
Representation
Resource Type Dataset
Format application/json; text/markdown; text/tab-separated-values; application/octet-stream
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Version 2.0
Discipline Computer Science; Computer Science, Electrical and System Engineering; Construction Engineering and Architecture; Engineering; Engineering Sciences; Life Sciences; Medicine; Neurosciences