TILES-2018 is a longitudinal physiologic and behavioral dataset of hospital workers collected for workplace stress and performance research. Multimodal sensor, environmental, and contextual streams were recorded from hospital nurses and staff at USC Keck Hospital, with daily questionnaire labels. The Scientific Data paper describes 212 participants.
- Type
- Dataset
- Licence
- Not reported
- Access
- Not reported
- Subjects
- 212
- PPG sites
- None
- Setting
- Clinical
- Wrist
- Not reported
- Raw waveforms
- Not reported
- Tasks
- Stress
- Updated
- Oct 27, 2026
Original description
We present a novel longitudinal multimodal corpus of physiological and behavioral data collected from direct clinical providers in a hospital workplace. We designed the study to investigate the use of off-the-shelf wearable and environmental sensors to understand individual-specific constructs such as job performance, interpersonal interaction, and well-being of hospital workers over time in their natural day-to-day job settings. We collected behavioral and physiological data from n = 212 participants through Internet-of-Things Bluetooth data hubs, wearable sensors (including a wristband, a biometrics-tracking garment, a smartphone, and an audio-feature recorder), together with a battery of surveys to assess personality traits, behavioral states, job performance, and well-being over time. Besides the default use of the data set, we envision several novel research opportunities and potential applications, including multi-modal and multi-task behavioral modeling, authentication through biometrics, and privacy-aware and privacy-preserving machine learning.
Verbatim fromthe publisher's DOI record· Publisher licence: https://creativecommons.org/licenses/by/4.0

Key numbers
How it works
- Reference labels
- stress, questionnaire
- Device roles
- Study wearable (IMU)
Leaderboard rows· 1
All leaderboards| Task | Dataset | Metric | Value | Rank |
|---|---|---|---|---|
| Stress detection (acute / prolonged / affect) | TILES-2018 | Accuracy ↑ | 0.631 | #1 / 1 |
Models trained or evaluated on it· 1
Papers using it· 1
FAQ
How many subjects are in TILES-2018?
TILES-2018 has data from 212 subjects, as listed in its research record.
What signals does TILES-2018 include?
TILES-2018 includes PPG, IMU and ECG data.
What can TILES-2018 be used for?
Research tasks it supports: stress detection. Reference labels: stress and questionnaire.
How do I get TILES-2018, and what is its licence?
It is available from https://tiles-data.isi.edu/. No licence is recorded for it here, so check the terms on the source page before you use it.
Which models and papers in the ChatPPG research hub use TILES-2018?
The hub links it to 1 paper, including "Beyond Latent Personalization: Integrating HRV-Conditioned Personalization via LLM for Interpretable Stress Detection". They are listed under Related on this page.
Cite
APA
TILES-2018 [Data set]. (n.d.). usc-isi. https://doi.org/10.1038/s41597-020-00655-3
BibTeX
@misc{tiles2018tiles2018,
title = {{TILES-2018}},
howpublished = {usc-isi},
doi = {10.1038/s41597-020-00655-3}
}Built from the hub record. Check it against the publisher before submitting.
Cite the ChatPPG record
Cite the dated snapshot 2026-10 for a fixed, reproducible version. Please also cite the original publications listed above.
APA
ChatPPG. (2026). TILES-2018: dataset record (Version 2026-10) [Data set]. ChatPPG Research Hub. https://chatppg.com/research/datasets/tiles-2018
BibTeX
@misc{chatppg_dataset_tiles_2018,
author = {{ChatPPG}},
title = {{TILES-2018: dataset record}},
year = {2026},
month = oct,
version = {2026-10},
howpublished = {\url{https://chatppg.com/research/datasets/tiles-2018}},
note = {ChatPPG Research Hub, Snapshot 2026-10, https://chatppg.com/research/snapshots/2026-10}
}CITATION.cff
cff-version: 1.2.0 message: "If you use this resource, please cite it as below." type: dataset title: "TILES-2018: dataset record" authors: - name: "ChatPPG" url: "https://chatppg.com/research/datasets/tiles-2018" repository-artifact: "https://chatppg.com/research/snapshots/2026-10" version: "2026-10" date-released: "2026-10-27"
History
Record updated
Papers
Beyond Latent Personalization: Integrating HRV-Conditioned Personalization via LLM for Interpretable Stress DetectionUses TILES-2018arXiv 2610.23555v1 · 2026
A cross-subject stress recognition method integrating bidirectional cross-modal multi-path fusion and adaptive adversarial learning (WESAD; in Chinese)Same task: StressSheng Wu Yi Xue Gong Cheng Xue Za Zhi · 2026
Calibrated photoplethysmography-derived heart rate variability approximates electrocardiographic gold-standard performance for stress-state classificationSame task: StressSpringer Science and Business Media LLC · 2026
