Cross-domain task-load dataset Accepted · IJHCI 2026, in press

REVELIO

REVELIO extends ADABase with two commercial video games, Hogwarts Legacy broom flight and Overcooked! 2, alongside the n-back protocol, recorded with the same sensors and annotation scheme.

Together with ADABase: 96 sessions from 83 unique participants across four applications · n-back, driving simulator and two games.

Request access Read paper (preprint) Documentation notebook BibTeX
Face landmarks and AU extraction synced with physiological signals
Multimodal extraction
Facial action units aligned with ECG · EDA · PPG · respiration
Participant in the instrumented cabin during a game session
In-cabin game experiment
Xbox controller · eye-tracker · RGB camera on the shared rig
Dataset at a glance
Participants
37
Sessions
45 (30 public)
Tasks
3 n-back + 2 games
Format
HDF5
Biosignals
ECG, PPG, EDA, EMG, RSP, SKT · stored at 1 kHz
Eye / Video
Gaze & pupil (250 Hz), facial AUs & body landmarks (no raw video)
Labels
NASA-TLX, performance, meta-information · fully ADABase compatible
License
Academic-only EULA
Access · academic use only

Request the dataset

01
Check eligibility
Permanent position at an academic institution, institutional email address, non-commercial academic research only.
02
Request on Zenodo
Use Request access on the Zenodo record. State name, position, affiliation, postal address, institutional email, up to five co-researchers and the intended research use.
03
Accept the EULA
Submitting the request accepts the End User License Agreement. Access is granted once the request has been reviewed.
REVELIO Public Set on Zenodo ADABase Public Set on Zenodo Read the EULA

The Private Set (15 sessions) is retained as a hidden test set for benchmarking. Access is free of charge. Questions and commercial inquiries: adabase@iis.fraunhofer.de

Documentation

Loading the public sets

A Jupyter notebook walks through the ADABase and REVELIO public sets end to end, from the HDF5 layout to model-ready windows with a subject-wise split. Driving and gaming files share one layout, so the same code reads both.

View in browser Notebook (.ipynb) on GitHub
  1. 01Files, tables and channels: SIGNALS, SUBJECTIVE, PERFORMANCE, META
  2. 02Participants and protocol, annotation by STUDY, PHASE, LEVEL
  3. 03NASA-TLX ratings and task performance per level
  4. 04Biosignals, downsampling to 100 Hz and normalization
  5. 05Window selection and building the dataset
  6. 06Suggested subject-wise split of the public sets
Cite

Cite this dataset

Please cite the Zenodo records you use and both papers: ADABase introduced the acquisition setup, and REVELIO extends it with the gaming cohort.

Oppelt, M.P.; Foltyn, A.; Lang-Richter, N.R.; Eskofier, B.M. REVELIO: Multimodal Task Load Estimation for Cross-Domain Generalization. International Journal of Human–Computer Interaction 2026, in press. Preprint: doi:10.48550/arXiv.2509.01642

Oppelt, M.P.; Foltyn, A.; Deuschel, J.; Lang, N.R.; Holzer, N.; Eskofier, B.M.; Yang, S.H. ADABase: A Multimodal Dataset for Cognitive Load Estimation. Sensors 2023, 23(1), 340. doi:10.3390/s23010340

BIBTEX
@article{oppelt2026revelio,
  author    = {Oppelt, Maximilian P. and Foltyn, Andreas
               and Lang-Richter, Nadine R. and Eskofier, Bjoern M.},
  title     = {{REVELIO}: Multimodal Task Load Estimation
               for Cross-Domain Generalization},
  journal   = {International Journal of Human--Computer Interaction},
  publisher = {Taylor \& Francis},
  year      = {2026},
  doi       = {10.48550/arXiv.2509.01642},
  note      = {In press. DOI refers to the arXiv preprint arXiv:2509.01642}
}

@article{oppelt2023adabase,
  author  = {Oppelt, Maximilian P. and Foltyn, Andreas and Deuschel, Jessica
             and Lang, Nadine R. and Holzer, Nina and Eskofier, Bjoern M.
             and Yang, Seung Hee},
  title   = {{ADABase}: A Multimodal Dataset for Cognitive Load Estimation},
  journal = {Sensors},
  year    = {2023},
  volume  = {23},
  number  = {1},
  pages   = {340},
  doi     = {10.3390/s23010340}
}
Zenodo records & identifiers
RecordSessionsDOI
ADABase: Cognitive Driving Public Set3010.5281/zenodo.24051552
REVELIO: Cognitive Gaming Public Setthis dataset3010.5281/zenodo.24060698
Paper: IJHCI 2026 · in press Preprint: arXiv:2509.01642 ADABase paper: 10.3390/s23010340