Contactless Vital Sign Monitoring for Multiple People Using a Millimeter-wave MIMO Radar

Radar technology offers much appeal for contactless vital sign monitoring. While most radar-based approaches achieve reasonable performance for single-person scenarios, they suffer from inaccurate vital sign estimates for multiple individuals, especially when the subjects occupy the same range bin. In addition, complex interferences due to environmental clutter and random body movements (RBMs) further exacerbate the issue of poor performance. We propose a resonance-based sparse separation (RBSS) algorithm for contactless vital sign measurement using millimeter wave (mmWave) multiple-input multiple-output (MIMO) radar. The proposed algorithm utilizes the resonance-based signal decomposition and can achieve reliable reconstruction of cardiopulmonary signals and precise estimates of respiration rate (RR) and heart rate (HR) for multiple individuals located within the same range bin. Experiment results demonstrate the efficacy of the proposed method, even under conditions of heavy clutter and moderate RBMs.

Authors

Institutions

Publication Details

Published
2025-03-12
DOI
https://doi.org/10.1109/icassp49660.2025.10890100
Citations
3
Primary Topic
Non-Invasive Vital Sign Monitoring
Type
article
Field-Weighted Citation Impact
2.02

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Contactless Vital Sign Monitoring for Multiple People Using a Millimeter-wave MIMO Radar

Andy W. H. Khong, Xiaoling Fu, Ritesh Chandra Tewari, Xingze Wang et al.
3 citations
Non-Invasive Vital Sign Monitoring
2.02
article

Contactless Vital Sign Monitoring for Multiple People Using a Millimeter-wave MIMO Radar

Andy W. H. Khong, Xiaoling Fu, Ritesh Chandra Tewari, Xingze Wang, Yuan Liu
article en
3 citations

Abstract

Radar technology offers much appeal for contactless vital sign monitoring. While most radar-based approaches achieve reasonable performance for single-person scenarios, they suffer from inaccurate vital sign estimates for multiple individuals, especially when the subjects occupy the same range bin. In addition, complex interferences due to environmental clutter and random body movements (RBMs) further exacerbate the issue of poor performance. We propose a resonance-based sparse separation (RBSS) algorithm for contactless vital sign measurement using millimeter wave (mmWave) multiple-input multiple-output (MIMO) radar. The proposed algorithm utilizes the resonance-based signal decomposition and can achieve reliable reconstruction of cardiopulmonary signals and precise estimates of respiration rate (RR) and heart rate (HR) for multiple individuals located within the same range bin. Experiment results demonstrate the efficacy of the proposed method, even under conditions of heavy clutter and moderate RBMs.

Nanyang Technological University (SG)
Delta
Openalex Percentile: Top 15%
Non-Invasive Vital Sign Monitoring
2.02
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.