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Data Integration Using Multivariate Mode Decomposition for Physiological Sensing with Multiple Millimeter-Wave Radar Systems

Signal Processing 2025-10-14 v1

Abstract

This study proposes a multi-radar system for non-contact physiological sensing across arbitrary body orientations. In integrating signals obtained from different radar viewpoints, we adopt a multivariate variational mode decomposition method to extract the common respiratory component. Experiments conducted with six subjects under varying distances and orientations demonstrate that, compared with a single-radar setup, the proposed system reduced the root mean square error of the respiratory interval by 35.5%, decreased the mean absolute error of the respiratory rate by 30.8%, and improved accuracy by 9.4 percentage points. These results highlight that combining multiple radar viewpoints with signal integration enables stable respiratory measurement regardless of body orientation.

Keywords

Cite

@article{arxiv.2510.10542,
  title  = {Data Integration Using Multivariate Mode Decomposition for Physiological Sensing with Multiple Millimeter-Wave Radar Systems},
  author = {Kimitaka Sumi and Takuya Sakamoto},
  journal= {arXiv preprint arXiv:2510.10542},
  year   = {2025}
}

Comments

7 pages, 4 figures, 5 tables. This work is going to be submitted to the IEEE for possible publication

R2 v1 2026-07-01T06:32:07.802Z