Measurements of body-composition changes are important for assessing patients' nutritional status and the progression of diseases such as sarcopenia, cachexia, atrophy, and cancer. Ultrasound imaging is the preferred technique for direct body-composition measurements owing to its accessibility, ease of use, and non-invasiveness. Typically, ultrasound imaging techniques use echogenicity changes to identify the interface between different tissue layers, resulting in time-consuming measurements with accuracies that depend on the ultrasound image quality. Radio frequency (RF) signals obtained directly from an ultrasound system ensure the reproducibility of measurements.

This study proposes a two-dimensional ultrasound signal-processing technique for measuring body composition.

Backscattered RF signals were acquired from the forearms of human subjects using an ultrasound system. The interfaces of subcutaneous fat, muscle, and bone were identified using the proposed signal processing technique for RF signals and ultrasound imaging. The longitudinal-sectional areas of the subcutaneous fat and muscle measured using ultrasound signals were validated by comparison with those measured using ultrasound imaging.

The results of the proposed technique and ultrasound imaging exhibited strong linear correlation. The area correlations between the proposed technique and ultrasound imaging were 0.937 and 0.991 for subcutaneous fat and muscle, respectively.

The proposed technique demonstrates feasibility of clinical applications by performing an in vivo human study.