nm000106 NEMAR-native dataset

FRL Handwriting: Handwriting Decoding from Surface Electromyography

This dataset comprises wrist-based surface electromyography (sEMG) recordings from 100 participants performing imagined handwriting tasks. Participants wrote prompted text in air without a physical writing surface, using a 16-channel sEMG wristband sampled at 2000 Hz. The dataset includes approximately 700 sessions (~7 per participant) and serves as a benchmark for developing non-invasive neuromotor interfaces for text entry in augmented/virtual reality and mobile computing applications.

EMG
Issues GitHub

Download this dataset

Pick a method. Large datasets skip the zip and use the streaming methods below — all resumable. Full download guide →

  1. Download archive (.zip) — 26.9 GB

    A single zip of the published version. Best for small/medium datasets.

    Download zip

  2. NEMAR CLI recommended

    Pulls the pinned version + annexed data and resumes cleanly. Install nemar-cli → 

    nemar dataset download nm000106
  3. DataLad

    Clone the dataset repo and fetch file content on demand. Docs → 

    datalad clone https://github.com/nemarDatasets/nm000106 nm000106
cd nm000106 && datalad get .
  4. git-annex

    Plain git + git-annex against the dataset repo. Docs → 

    git clone https://github.com/nemarDatasets/nm000106 nm000106
cd nm000106 && git annex get .
  5. Direct files (wget / curl / rclone)

    Every file with a stable, range-resumable URL from the manifest. Needs curl, jq, wget (or rclone/aria2c). Docs → 

    curl -s https://data.nemar.org/nm000106/v2.0.0/manifest.json | jq -r '.[].bytes_url' > urls.txt
wget -xc -i urls.txt

Compute on this dataset

Two routes today, with a third (in-browser one-click submission) landing soon.

  1. NeuroScience Gateway (NSG) portal.

    NSG runs EEGLAB / Brainstorm / MNE pipelines on supercomputing time donated by SDSC. Create an account, point a job at this dataset's S3 prefix (s3://nemar/nm000106), and submit.
    nsgportal.org →

  2. Local processing with nemar-cli.

    Pull the dataset to your machine and run any toolbox locally. Honors the published version pinning. 

    npm install -g nemar-cli
nemar dataset clone nm000106
cd nm000106 && nemar dataset get
  3. Just the files.

    rclone, aria2c, or any HTTPS client works against data.nemar.org/nm000106/ — the manifest carries presigned S3 URLs.

Direct compute access is coming soon. One-click NSG submission from this page is scoped for a follow-up phase. Tracked on nemarOrg/website#6.

Citations

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    Files

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    Signal viewer
    How to use the data (for agentic research) license, citation, download commands

    What it is

    Modalities
    EMG
    Participants
    100
    Size
    45.3 GB
    Tasks
    handwriting

    License and terms

    License
    CC-BY-NC 4.0
    Note
    Non-commercial use only (CC-BY-NC 4.0).
    Recommended citation
    Kaifosh, P., Reardon, T. R., & Labs, C. A. R. (2026). FRL Handwriting: Handwriting Decoding from Surface Electromyography (Version v2.0.0) [Data set]. NEMAR. https://doi.org/10.82901/nemar.nm000106
    Reference
    https://doi.org/10.1038/s41586-025-09255-w

    Where the bytes are

    Latest version (always current)
    https://data.nemar.org/nm000106/latest/
    This version (v2.0.0)
    https://data.nemar.org/nm000106/v2.0.0/

    How to download

    The dataset
    nemar dataset download nm000106 Clones and fetches in one step. Content under stimuli/ and derivatives/ is skipped by default because those trees can be large; add --stimuli --derivatives for the whole thing.
    A subset, one step
    nemar dataset download nm000106 --subjects sub-01,02 Also filters by --sessions, --tasks, --runs, --datatypes, --include and --exclude.
    A subset, step 1
    nemar dataset clone nm000106 Clones git-annex pointers only; fetches no file content. Creates ./nm000106.
    A subset, step 2
    cd nm000106 The get command below reads the clone's annex, so it only works from inside the clone.
    A subset, step 3
    nemar dataset get <files> Pulls the files you actually need. Skips stimuli/ and derivatives/ unless the path you ask for is under one of them.
    One small file
    https://data.nemar.org/nm000106/v2.0.0/participants.tsv A direct HTTPS fetch works for any single file.

    Assess fit without downloading

    Participants table
    https://data.nemar.org/nm000106/v2.0.0/participants.tsv
    Dataset description
    https://data.nemar.org/nm000106/v2.0.0/dataset_description.json
    Directory listing
    https://data.nemar.org/nm000106/v2.0.0/?format=json
    Catalog record
    https://api.nemar.org/datasets/nm000106