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Updated: May 16, 2026
06:48
Clinical Anthropometrics and Body Composition from 3-Dimensional Optical Imaging
Published on: June 7, 2024
Consumer Technologies for Personalized Health: Feasibility of Five-Compartment Body Composition Self-Assessment Using
Jonathan P Bennett1, Michael C Wong1,2, Yong En Liu1
1Department of Epidemiology, University of Hawai'i Cancer Center, Honolulu, Hawaii, USA.
Obesity (Silver Spring, Md.)
|May 14, 2026
Summary
Consumer smartphones and smartwatches can accurately monitor body composition. This technology enables precise, low-cost body composition analysis outside clinical settings, aiding nutritional status assessment.
Area of Science:
- Biomedical Engineering
- Human Physiology
- Health Informatics
Background:
- Accurate body composition monitoring is crucial for assessing nutritional status and detecting sarcopenia.
- Traditional methods for body composition analysis are often confined to clinical settings, limiting accessibility.
- There is a need for accessible, personalized, and data-driven methods for continuous body composition monitoring.
Purpose of the Study:
- To evaluate a novel self-assessment model for body composition monitoring using consumer technologies.
- To integrate smartphone-based 3D optical imaging and smartwatch-based bioelectrical impedance analysis into a five-compartment model.
- To assess the accuracy of this consumer-technology-based model against laboratory standards.
Main Methods:
- Developed a five-compartment model combining smartphone-derived body volume and smartwatch-derived total body water.
- Calibrated body volume and total body water measurements against gold-standard methods (air displacement plethysmography and clinical bioimpedance).
- Compared estimates from the consumer model with laboratory-derived five-compartment estimates using regression analysis and RMSE.
Main Results:
- Smartphone body volume and smartwatch total body water showed high agreement with laboratory measures (r² > 0.97) after bias correction.
- The calibrated consumer model accurately estimated fat-free mass and fat mass, closely matching laboratory results (r² > 0.96).
- The model demonstrated strong performance in a cohort of 30 adults.
Conclusions:
- Calibrated smartphones and smartwatches provide reliable multicompartment body composition estimates comparable to laboratory methods.
- This approach enables precise, low-cost body composition monitoring in diverse settings, including remote and resource-limited environments.
- Consumer technologies offer a viable solution for personalized and data-driven health monitoring.
