The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/48acba04-96bc-4131-b52f-9e18458ad92b

Sadeghi, Ehsan; chiumento, Alessandro; Havinga, Paul (2024): mm-Wave FMCW Radar Vital Sign Monitoring Dataset: Diverse Physiological Scenarios. Version 2. 4TU.ResearchData. dataset. https://doi.org/10.4121/48acba04-96bc-4131-b52f-9e18458ad92b.v2

Dataset

x choose version: version 1 - 2024-04-05

• Artificial Intelligence and Image Processing
• Electrical and Electronic Engineering
• Data Format
• Health and Support Services
• Distributed Computing
• Biomedical Engineering
• Physiology
• Engineering
• Health
• Technology
• Information and Computing Sciences
• Biological Sciences
• Medical and Health Sciences

Dataset, Heart rate, mm-wave FMCW Radar, Respiratory rate, TI AWR1642, Vital sign detection

CC BY-NC-SA 4.0

RefWorks, BibTeX, Reference Manager, Endnote, DataCite, NLM, DC, CFF

by Ehsan Sadeghi , Alessandro chiumento, Paul Havinga

This dataset contains vital sign measurements (heart rate and respiratory rate) from mm-wave Frequency-Modulated Continuous Wave (FMCW) radar. It includes data from ten participants across scenarios like resting, elevated heart rate activities, and accounts for extreme physiological conditions such as asthma and meditation. Each record is validated against the Polar H10 sensor. The dataset is structured to facilitate research in non-invasive health monitoring, providing ADC samples, range maps, and chest displacement signals.

Note: The detailed guide for this data set can be found in "https://doi.org/10.48550/arXiv.2405.12659". In the case of using it please cite this article.

• 2024-04-05 first online

• 2024-06-18 published, posted

4TU.ResearchData

Binary files/ CSV files

Comprehensive mm-Wave FMCW Radar Dataset for Vital Sign Monitoring: Embracing Extreme Physiological Scenarios

• https://doi.org/10.48550/arXiv.2405.12659

• NWO ENW grant Dutch Research Council

University of Twente, Faculty Of Electrical Engineering, Mathematics and Computer Science, Pervasive Systems Group.