Trade-Offs in FMCW Radar-Based Respiration and Heart Rate Variability

TL;DR

This paper evaluates a low-cost FMCW MIMO radar for non-contact vital sign monitoring, analyzing how distance and chirp count affect accuracy in estimating respiratory and heart rates, revealing a fundamental trade-off between robustness and resolution.

Contribution

It provides a systematic experimental assessment of FMCW radar performance for vital sign monitoring, highlighting the impact of sensing parameters on measurement accuracy and limitations in high-resolution tracking.

Findings

Optimal performance at ~70cm distance with errors of 0.8 bpm (RR) and 3.2 bpm (HR)

Chirp count of at least 96 improves measurement stability

Limited accuracy in capturing beat-to-beat and breath-to-breath variability

Abstract

This study presents a comprehensive experimental assessment of a low-cost frequency-modulated continuous-wave (FMCW) multiple-input multiple-output (MIMO) radar for non-contact vital sign monitoring, focusing on respiratory rate (RR) and heart rate (HR) estimation. The influence of sensing distance and number of transmitted chirps on measurement accuracy is systematically quantified. Results exhibit a U-shaped error profile with optimal performance near $70~cm$, achieving mean absolute errors of $0.8~bpm$ for RR and $3.2~bpm$ for HR. Accuracy deteriorates at short ($<60~cm$) and long ($>100~cm$) distances due to multipath, near-field, and signal-to-noise effects. Increasing chirp count enhances performance: RR errors converge asymptotically for $\geq96$ chirps, while HR requires at least 96 chirps for stable detection. Variability metrics, including heart and respiratory rate variability, remain less accurate ($>15$--$30\%$ error), indicating limited capability in capturing instantaneous fluctuations. These findings define a fundamental trade-off: the radar ensures robust estimation of average RR and HR but exhibits restricted precision in high-resolution beat-to-beat and breath-to-breath monitoring.