ArticleSensors (Basel, Switzerland)2022
mm-Wave Radar-Based Vital Signs Monitoring and Arrhythmia Detection Using Machine Learning.
Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.
What it found
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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
18 citing papers in PubMed, 1 synthesis or guideline pooled it, 75 citations in OpenAlex.
- Systematic Literature Review Regarding Heart Rate and Respiratory Rate Measurement by Means of Radar Technology.Sensors (Basel, Switzerland) · 2024Pooled it
- Estimation of Compression Depth During CPR Using FMCW Radar with Deep Convolutional Neural Network.Sensors (Basel, Switzerland) · 2025Article
- Non-Contact Heart Rate Variability Monitoring with FMCW Radar via a Novel Signal Processing Algorithm.Sensors (Basel, Switzerland) · 2025Article
- A Comprehensive Survey of Research Trends in mmWave Technologies for Medical Applications.Sensors (Basel, Switzerland) · 2025Review
- Motion Cancellation Technique of Vital Signal Detectors Based on Continuous-Wave Radar Technology.Sensors (Basel, Switzerland) · 2025Review
- Radar Signal Processing and Its Impact on Deep Learning-Driven Human Activity Recognition.Sensors (Basel, Switzerland) · 2025Article
- Contactless and short-range vital signs detection with doppler radar millimetre-wave (76-81 GHz) sensing firmware.Healthcare technology letters · 2024Article
- Implementation of a digital distress detection system in palliative care: qualitative data on perspectives of a multiprofessional palliative care team.BMC palliative care · 2024Article
- Contactless vital signs monitoring in macaques using a mm-wave FMCW radar.Scientific reports · 2024Article
- Contactless Heart and Respiration Rates Estimation and Classification of Driver Physiological States Using CW Radar and Temporal Neural Networks.Sensors (Basel, Switzerland) · 2023Article
- Soli-enabled noncontact heart rate detection for sleep and meditation tracking.Scientific reports · 2023Article
- Recent Progress in Micro- and Nanotechnology-Enabled Sensors for Biomedical and Environmental Challenges.Sensors (Basel, Switzerland) · 2023Review
- Few-Shot User-Adaptable Radar-Based Breath Signal Sensing.Sensors (Basel, Switzerland) · 2023Article
- Doppler radar remote sensing of respiratory function.Frontiers in physiology · 2023Review
- Real-Time Non-Contact Millimeter Wave Radar-Based Vital Sign Detection.Sensors (Basel, Switzerland) · 2022Article
- Effects of Receiver Beamforming for Vital Sign Measurements Using FMCW Radar at Various Distances and Angles.Sensors (Basel, Switzerland) · 2022Article
- Non-Invasive Data Acquisition and IoT Solution for Human Vital Signs Monitoring: Applications, Limitations and Future Prospects.Sensors (Basel, Switzerland) · 2022Review
- Low-Complexity Joint 3D Super-Resolution Estimation of Range Velocity and Angle of Multi-Targets Based on FMCW Radar.Sensors (Basel, Switzerland) · 2022Article
Corrections and comments
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
Abstract
A non-contact, non-invasive monitoring system to measure and estimate the heart and breathing rate of humans using a frequency-modulated continuous wave (FMCW) mm-wave radar at 77 GHz is presented. A novel diagnostic system is proposed which extracts heartbeat phase signals from the FMCW radar (reconstructed using Fourier series analysis) to test a three-layer artificial neural network model to predict the presence of arrhythmia in individuals. The effect of person orientation, distance of measurement and movement was analyzed with respect to a reference device based on statistical measures that include number of outliers, mean, mean squared error (MSE), mean absolute error (MAE), median absolute error (medAE), skewness, standard deviation (SD) and R-squared values. The individual oriented in front of the radar outperformed almost all other orientations for most distances with an expected d = 90 cm and d = 120 cm. Furthermore, it was found that the heart rate that was measured while walking and the breathing rate which was measured for a motionless individual generated results with the lowest SD and MSE. An artificial neural network (ANN) was trained using the MIT-BIH database with a training accuracy of 93.9 % and an R
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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.