ArticleScientific reports2025
Detection of vital signs based on millimeter wave radar.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Extensive Age-Balanced and Subject-Varied mmWave Radar Dataset of Referenced Records for Vital Signs.Scientific data · 2026Article
- A radar vital signs detection method in complex environments.Scientific reports · 2026Article
- Non-Contact Measurement of Human Vital Signs in Dynamic Conditions Using Microwave Techniques: A Review.Sensors (Basel, Switzerland) · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
With the growing demand for health monitoring, non-contact vital signs monitoring technology has garnered widespread attention. While traditional health monitoring methods are accurate, they have limitations in terms of non-contact and non-invasive capabilities. This paper proposes a non-contact vital signs monitoring method based on frequency modulated continuous wave (FMCW) millimeter-wave radar, named MRVS, to enhance both convenience and accuracy. The method consists of three steps: signal processing, decomposition, and reconstruction. Firstly, the millimeter-wave radar is used to detect chest movements, extracting both respiration and heartbeat signals. Then, combining signal superposition with phase difference techniques effectively eliminates static clutter and respiratory harmonic interference, enhancing the signal. Next, discrete wavelet transform (DWT) is utilized to suppress clutter and noise further, performing signal decomposition. The reconstruction module employs an adaptive Kalman filter (AKF) combined with square root normalization for accurate heart rate estimation. Experimental results demonstrate that this method achieves an estimation error rate of less than 7% under different distances, angles, and postures, showcasing high accuracy and robustness and providing a new solution for non-contact vital signs monitoring.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.