UWB-Fat: Non-Intrusive Body Fat Measurement Using Commodity Ultra-Wideband Radar
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arXiv
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| Autores principales: | , , , , , , , , |
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| Formato: | Preprint |
| Publicado: |
2026
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| _version_ | 1866915995702001664 |
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| author | Li, Haotang Ren, Yili Qi, Zhenyu He, Sen Peng, Kebin Tan, Sheng Liu, Bo Zhao, Jiyue Wang, Zi |
| author_facet | Li, Haotang Ren, Yili Qi, Zhenyu He, Sen Peng, Kebin Tan, Sheng Liu, Bo Zhao, Jiyue Wang, Zi |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2605_08403 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | UWB-Fat: Non-Intrusive Body Fat Measurement Using Commodity Ultra-Wideband Radar Li, Haotang Ren, Yili Qi, Zhenyu He, Sen Peng, Kebin Tan, Sheng Liu, Bo Zhao, Jiyue Wang, Zi Medical Physics Human-Computer Interaction 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. |
| title | UWB-Fat: Non-Intrusive Body Fat Measurement Using Commodity Ultra-Wideband Radar |
| topic | Medical Physics Human-Computer Interaction |
| url | https://arxiv.org/abs/2605.08403 |