Wital: A COTS WiFi Devices Based Vital Signs Monitoring System Using NLOS Sensing Model
Not on the map. Why?
Abstract (arXiv)
Vital sign (breathing and heartbeat) monitoring is essential for patient care and sleep disease prevention. Most current solutions are based on wearable sensors or cameras; however, the former could affect sleep quality, while the latter often present privacy concerns. To address these shortcomings, we propose Wital, a contactless vital sign monitoring system based on low-cost and widespread commercial off-the-shelf (COTS) Wi-Fi devices. There are two challenges that need to be overcome. First, the torso deformations caused by breathing/heartbeats are weak. How can such deformations be effectively captured? Second, movements such as turning over affect the accuracy of vital sign monitoring. How can such detrimental effects be avoided? For the former, we propose a non-line-of-sight (NLOS) sensing model for modeling the relationship between the energy ratio of line-of-sight (LOS) to NLOS signals and the vital sign monitoring capability using Ricean K theory and use this model to guide the system construction to better capture the deformations caused by breathing/heartbeats. For the latter, we propose a motion segmentation method based on motion regularity detection that accurately distinguishes respiration from other motions, and we remove periods that include movements such as turning over to eliminate detrimental effects. We have implemented and validated Wital on low-cost COTS devices. The experimental results demonstrate the effectiveness of Wital in monitoring vital signs.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). First posted on arXiv 23 May 2023.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2024: 2; 2025: 2; 2026: 2.
6 papers.
- 2024WiOpen: A Robust Wi-Fi-based Open-set Gesture Recognition Frameworkcited by 16
- 2026Breaking Coordinate Overfitting: Geometry-Aware WiFi Sensing for Cross-Layout 3D Pose Estimationcited by 2
- 2025PulseFi: A Low Cost Robust Machine Learning System for Accurate Cardiopulmonary and Apnea Monitoring Using Channel State Informationcited by 1
- 2026Beyond Physical Labels: Redefining Domains for Robust WiFi-based Gesture Recognitioncited by 1
- 2024Towards Battery-Free Wireless Sensing via Radio-Frequency Energy Harvestingcited by 0
- 2025MobiVital: Self-supervised Time-series Quality Estimation for Contactless Respiration Monitoring Using UWB Radarcited by 0
- 2026Breaking Coordinate Overfitting: Geometry-Aware WiFi Sensing for Cross-Layout 3D Pose Estimation18 Jan 2026
- 2026Beyond Physical Labels: Redefining Domains for Robust WiFi-based Gesture Recognition7 Jan 2026
- 2025PulseFi: A Low Cost Robust Machine Learning System for Accurate Cardiopulmonary and Apnea Monitoring Using Channel State Information15 Oct 2025
- 2025MobiVital: Self-supervised Time-series Quality Estimation for Contactless Respiration Monitoring Using UWB Radar14 Mar 2025
- 2024Towards Battery-Free Wireless Sensing via Radio-Frequency Energy Harvesting26 Aug 2024
- 2024WiOpen: A Robust Wi-Fi-based Open-set Gesture Recognition Framework1 Feb 2024