Abstract
In previous work, we introduced an ‘invisible’ ECG system with electrodes integrated into a toilet seat, capturing signals from the thighs. Here, we present the tOLIet dataset with single-lead thigh ECGs to advance cardiovascular assessment using this novel approach. The dataset includes 149 records from 86 individuals (50 females, 36 males; mean age 31.73 ± 13.11 years; weight 66.89 ± 10.70 kg; height 166.82 ± 6.07 cm). Participants were recruited via the Centro Hospitalar Universitário de Lisboa Central (CHULC). Each recording features four differential signals from toilet-seat electrodes alongside reference data from a hospital-grade 12-lead ECG. Beyond signal collection and quality evaluation, we conducted a gender-specific analysis comparing valid signal percentages relative to Body Mass Index (BMI). This analysis explores anatomical or physiological factors affecting thigh-based ECG acquisition, guiding system design and customization to enhance signal reliability across populations.
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Data availability
The dataset is available at PhysioNet21. The raw data in ‘csv’, ‘txt’ or ‘xml’ format was transformed into dictionaries containing the relevant data in matrices stored in DataFrame format.
Code availability
To pre-process the physiological data, we used the BioSPPy library (https://github.com/PIA-Group/BioSPPy), which contains modules for filtering the ECG signals, characteristics and data analysis; to analyse the statistical tests, we used the SciPy library (https://github.com/scipy/scipy). For more information on the raw or transformed data, code incompatibilities or other questions, please contact the corresponding author. The processing was carried out in Python 3.11.7, and the necessary code is available in the Scripts folder in PhysioNet21 to replicate it easily.
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Acknowledgements
This work is partially funded by National Funds through the Portuguese funding agency Fundação para a Ciência e a Tecnologia, I.P. (FCT, https://ror.org/00snfqn5816) within projects UID/50014/2025 - INESCTEC (https://doi.org/10.54499/UID/50014/2025), UID/50008/2025 - Instituto de Telecomunicações (https://doi.org/10.54499/UID/50008/2025) and LA/P/0063/2020, and grant 2022.10245.BDANA (https://doi.org/10.54499/2022.10245.BDANA). In addition, it is co-supported by the European Regional Development Fund (FEDER), through the Lisbon Regional Programme (LISBOA 2030) of the Portugal 2030 framework, under project LISBOA2030-FEDER-01318700 (ComSense). The authors would also like to thank OLI - Sistemas Sanitários S.A. for providing all the resources and support that made this work possible.
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A.S.S., M.V.C., S.M.L. and H.P.S. conceived the experiment(s). A.S.S. conducted the experiment(s). A.S.S., M.V.C. and H.P.S. analysed the results. All authors reviewed the manuscript.
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Silva, A.S., Correia, M.V., Laranjo, S.M. et al. Single-lead Thigh ECG Dataset (tOLIet) with Analysis of BMI Effects on Cardiac Signal Quality. Sci Data (2026). https://doi.org/10.1038/s41597-026-06713-6
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DOI: https://doi.org/10.1038/s41597-026-06713-6
