Extensive Age-Balanced and Subject-Varied mmWave Radar Dataset of Referenced Records for Vital Signs

Area of Science:

• Biomedical Engineering
• Signal Processing
• Medical Informatics

Background:

• Contactless vital signs monitoring is crucial for remote patient care and assisted living.
• Millimetre-wave (mmWave) radar offers a privacy-preserving solution for continuous health monitoring.
• Existing methods often lack comprehensive datasets for diverse populations and conditions.

Purpose of the Study:

• To present a novel dataset of vital signs acquired using mmWave radar technology.
• To facilitate the development and validation of algorithms for contactless vital signs extraction.
• To support research into the influence of demographics and physiological states on vital signs.

Main Methods:

• Collected mmWave radar data from 110 participants using two 60 GHz FMCW radars.
• Utilized a Class IIa medical device (ECG and accelerometer) as a reference standard.
• Recorded data across various postures, post-exercise, and breath-holding conditions.

Main Results:

• The dataset comprises vital signs measurements from a diverse population, including individuals with heart conditions.
• Includes extensive demographic and health status information for each participant.
• Provides synchronized radar, ECG, and accelerometer data for comprehensive analysis.

Conclusions:

• This dataset is a valuable resource for advancing contactless vital signs monitoring research.
• Enables testing of new algorithms for heart rate extraction and signal processing.
• Supports statistical studies on age-balanced and subject-varied populations for improved healthcare solutions.