A new dataset for millimeter-wave radar vital sensing with reference signals
Millimeter-wave (mmWave) radar is widely recognized as a critical tool for contactless, continuous human sensing across multiple scenarios. Yet, there is a lack of high-quality datasets with synchronized reference measurements, especially at higher frequencies, which are essential for advancing sign...
| Autores: | , , , , , |
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| Tipo de recurso: | conjunto de datos |
| Fecha de publicación: | 2026 |
| País: | España |
| Institución: | Consorci de Serveis Universitaris de Catalunya (CSUC) |
| Repositorio: | CORA.Repositori de Dades de Recerca |
| OAI Identifier: | oai:dnet:cora.rdr____::9cfd120c276b34a5cf496cc79ad52688 |
| Acceso en línea: | https://doi.org/10.34810/DATA2962 |
| Access Level: | acceso abierto |
| Palabra clave: | Engineering Medicine, Health and Life Sciences Cardiopulmonary activity Radar-based healthcare FMCW radar Vital signs monitoring Dataset |
| Sumario: | Millimeter-wave (mmWave) radar is widely recognized as a critical tool for contactless, continuous human sensing across multiple scenarios. Yet, there is a lack of high-quality datasets with synchronized reference measurements, especially at higher frequencies, which are essential for advancing signal processing methods and improving the retrieval of vital parameters. To address this gap, we introduce a new radar vital signal dataset collected with simultaneous reference recordings. The dataset is derived from measurements acquired using a custom-built, noncommercial radar system developed by our laboratory (CommSensLab-UPC) specifically for biomedical applications. The implemented Frequency-Modulated Continuous Wave (FMCW) radar system operates at 120 GHz within the industrial, scientific, and medical (ISM) band. This high center frequency provides superior spatial resolution and sensitivity to millimeter-level chest movements, enabling more precise monitoring of cardiopulmonary dynamics compared to lower-frequency systems. In parallel, a monitoring system records reference physiological signals, including electrocardiograms, respiratory traces, pulse waveforms, and blood pressure values. Under a predefined protocol, a professional clinician collected data from 24 healthy subjects, ensuring methodological rigor. The release of this dataset aims to facilitate the development and validation of advanced radar signal processing algorithms, thereby enhancing the contribution of radar technologies to hemodynamic monitoring and autonomic nervous system assessment. |
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