Abstract
We present a new dataset comprising radar, Electrocardiography (ECG), respiration, and inertial measurement signal recordings from 23 individuals while performing a series of simulated harmful behaviors. This dataset covers a range of actions across various levels of agitation and is especially well-suited for conducting research in health monitoring within high-risk clinical settings, such as inpatient psychiatric units. The dataset’s design prioritizes unrestricted, naturalistic behavior capture, providing valuable insights into real-world scenarios and supporting a wide range of applications. Although the dataset was initially designed for patient monitoring, the provided ECG and respiration recording extend the potential uses of the data to localization and non-contact vital sign measurement.
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Data availability
The dataset22 has been deposited to Zenodo23 and is available from https://doi.org/10.5281/zenodo.17565754.
Code availability
No custom code was used.
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Acknowledgements
This research has been supported by project 12215, funded by UK Research and Innovation (UK RI) as a Knowledge Transfer Partnership (KTP) action; project PID2023-150960NB-I00, funded by the Spanish Ministry of Science, Innovation and Universities and the European Union; project TED2021-129485B-C42, funded by MCIN/AEI/10.13039/501100011033 and the European Union “NextGenerationEU”/PRTR; and project AICO/2023/065, funded by Valencian Regional Government (Spain)
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All authors participated in the dataset design. B.T. conducted the data collection. N.R. supervised the collection. M.A. led the data validation. All authors wrote and reviewed the manuscript.
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Tilbury, B., Arevalillo-Herráez, M. & Ramzan, N. A multimodal dataset of harmful simulated behaviours in high-risk clinical settings using radar. Sci Data (2026). https://doi.org/10.1038/s41597-026-06703-8
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DOI: https://doi.org/10.1038/s41597-026-06703-8
