UWB-Fat: Non-Intrusive Body Fat Measurement Using Commodity Ultra-Wideband Radar

2026-05-08

AI Summary

This study addresses the longstanding trade-off between accuracy and accessibility in body fat measurement: clinical methods are costly and inconvenient, while consumer-grade devices often lack precision or require physical contact. To overcome these limitations, this work proposes a non-contact approach for estimating subcutaneous fat thickness using commercial ultra-wideband (UWB) radar. By leveraging the dielectric property differences among skin, adipose tissue, and muscle, the method extracts discriminative signal features and integrates them into a physics-informed model to achieve high-fidelity reconstruction. Validated across multiple anatomical sites in 15 participants, the technique attains a root-mean-square error of only 0.63 mm, demonstrating for the first time a low-cost, operator-free, and contactless solution for self-administered subcutaneous fat assessment—offering a practical pathway toward routine body composition monitoring.

Abstract

Body fat percentage and its spatial distribution are clinically important health indicators. However, existing measurement methods often impose a tradeoff between accuracy and accessibility. Clinical-grade techniques, such as Dual-Energy X-ray Absorptiometry (DEXA) and hydrostatic weighing, provide accurate measurements but require specialized equipment and trained operators, making them difficult to access and unsuitable for everyday use. In contrast, consumer-level methods, such as Bioelectrical Impedance Analysis (BIA) smart scales and skinfold calipers, are more accessible but typically provide only coarse-grained estimates, are prone to user error, or require intrusive physical contact. In this work, we present UWB-Fat, the first system that leverages commodity ultra-wideband (UWB) radar to enable non-intrusive, accessible, and accurate caliper-equivalent skinfold thickness estimation, serving as a convenient replacement for the skinfold caliper. UWB-Fat collects UWB signal at specified body sites non-intrusively without operator assistance. It extracts body-composition-related features from UWB signals by exploiting dielectric contrasts among skin, fat, and muscle tissues. Then, it uses a physics-inspired model to estimate site-specific skinfold thickness. We evaluate UWB-Fat on 15 participants, achieving a root mean square error of 0.63~mm for pooled-site subcutaneous fat thickness. These results highlight the potential of UWB-Fat to support low-cost, self-administered, and everyday body fat monitoring.

Problem

• body fat measurement
• accuracy vs. accessibility
• non-intrusive sensing
• skinfold thickness
• ultra-wideband radar

Innovation

• Ultra-Wideband (UWB) radar
• non-intrusive body fat measurement
• skinfold thickness estimation
• dielectric contrast
• physics-inspired modeling