Systematic Vital Signs Detection Framework Based on Frequency-Modulated Continuous Wave MIMO Radar
The frequency-modulated continuous wave (FMCW) radar has received much attention in the field of noncontact vital signs monitoring. However, since vital signs are usually very weak, it can be easily buried by interference and noise, especially for the heartbeat signal. To tackle this challenge, this article proposes a novel systematic vital signs detection framework using the multiple-input multiple-output FMCW radar. First, the signal noise ratio of the vital signs signal is enhanced by combining the phase signals of multiple channels using the maximum ratio combining method. Then, to suppress noise and interference, we construct the vital signs signal with singular spectral analysis and propose a correlation-based selection criterion to select potential intrinsic mode functions of the respiration and heartbeat signals. Finally, a fast independent component analysis is applied to extract the respiration signal, and the second-order derivative based fast independent component analysis in conjunction with an infinite impulse response notch filter is further developed to extract the heartbeat signal. Simulations and experimental results validate the effectiveness of the proposed framework.
Authors
- Mu Zhou (ORCID: https://orcid.org/0000-0003-3533-2227)
- Heng Liu (ORCID: https://orcid.org/0000-0002-8658-3686)
- Dusit Niyato (ORCID: https://orcid.org/0000-0002-7442-7416)
- Wei Xiang (ORCID: https://orcid.org/0000-0002-0608-065X)
- Yong Wang (ORCID: https://orcid.org/0000-0001-5061-8173)
- Jiacheng Wang (ORCID: https://orcid.org/0000-0003-1252-8761)
- Yu Pang (ORCID: https://orcid.org/0000-0002-7507-5387)
Institutions
- Chongqing University of Posts and Telecommunications (CN)
- Nanyang Technological University (SG)
- La Trobe University (AU)
Publication Details
- Journal
- IEEE Transactions on Industrial Informatics
- Published
- 2025-04-08
- DOI
- https://doi.org/10.1109/tii.2025.3545053
- Citations
- 9
- Primary Topic
- Non-Invasive Vital Sign Monitoring
- Type
- article
- Field-Weighted Citation Impact
- 6.07
Funders
- National Natural Science Foundation of China