Peer-reviewed research

White Papers

Independent and in-house research on 3D body data, digital anthropometry, body composition, and fit — validating Size Stream technology in research and clinical settings.

Machine Learning

Scan-over-Clothes (SOC): Improved Body Measurement Accuracy when Scanning Loose-Clothed Subjects

This paper introduces two innovations designed to reduce scan wear requirements for Size Stream's mobile scanning platform: the Body-Plus-Clothes (BPC) segmenter, which distinguishes between a subject's body and their clothing at the pixel level, and the Scan-Over-Clothes (SOC) Body Measurement Model, which uses BPC segmentation to compensate for loose clothing during body reconstruction and measurement prediction. Together, these advances are evaluated against existing algorithms to quantify the accuracy of trade-offs of scanning in loose versus tight-fitting clothing.

Gilmer et al. · 2025 Read paper →
Body Composition

Innovative digital approaches to characterize core factors of patients with late-stage knee osteoarthritis: a cross-sectional study

This first-of-its-kind study investigated the feasibility of using digital anthropometric tools, specifically Size Stream's Mobile Fit app, to assess body size and composition in patients with late-stage knee osteoarthritis scheduled for total knee arthroplasty. Alongside mobile 3D scanning, the study combined digital pain mapping and standardized physical performance tests to comprehensively characterize the clinical phenotypes of this patient population across varying levels of disability severity.

Minetto et al. · 2026 Read paper →
Body Composition

Improvements in 3D Body Shape and Measurement Accuracy from Size Stream

This paper documents the latest advancements to Size Stream's mobile 3D scanning platform, evaluating improvements in body fat percentage estimation, anthropometric measurement accuracy and repeatability, and 3D body shape reconstruction, particularly for users with high BMI. Using two studies, the research compares production algorithms from early 2025 against updated June and August 2025 releases, benchmarked against DXA and SS20 booth scanner data across a combined cohort of over 100 participants.

Hauser et al. · 2025 Read paper →
Body Composition

The impact of different body surface area prediction equations on ventricular dilatation prevalence in youth soccer players

This study aimed to assess the accuracy of different predictive equations for estimating body surface area (BSA) in youth soccer players and to evaluate how the choice of BSA normalization influences echocardiographic measures of ventricular size. By comparing 3D optical imaging-derived BSA with ten commonly used equations, the researchers sought to identify the most reliable formulas for athletic populations.

Busso et al. · 2025 Read paper →
Apparel & Sizing

A Comparative Anthropometric Analysis of U.S. Female Firefighters Versus the General Female Population

This study identifies significant anthropometric differences between U.S. female firefighters and the general female population, emphasizing the need for a specialized sizing system for personal protective clothing (PPC). Findings indicate that current PPC, often based on male or general female body measurements, leads to poor fit, increasing injury risks among female firefighters.

Bolaji et al. · 2025 Read paper →
Body Composition

Advancements in Body Composition Assessment Using Mobile Devices

The study discusses the development and evaluation of mobile 3D body scanning technology for assessing body composition. The study analyzed data from 209 scans of 118 individuals using the 4-compartment (4C) model for body composition, integrating multiple technologies like DXA and air displacement plethysmography.

Breck Sieglinger · 2024 Read paper →
Body Composition

Clinical Anthropometrics and Body Composition from 3-Dimensional Optical Imaging

The study highlights digital anthropometric systems providing quick, accurate body size and composition assessments through automated 3D avatars and reports. One system includes a rotating platform with cameras and a tablet, while the other uses a tablet on a stationary holder. These user-friendly tools are ideal for clinical and athletic applications, supporting personalized training and rehabilitation strategies.

Size Stream Research · 2024 Read paper →
Body Composition

Equations for Smartphone Prediction of Adiposity and Appendicular Lean Mass in Youth Soccer Players

The study investigates the reproducibility and validity of using smartphone-based digital anthropometry, specifically the Mobile Fit app, for predicting body composition in youth soccer players. The aim was to assess how well the app compares to the gold standard Dual-Energy X-ray Absorptiometry (DXA) in estimating body fat percentage and appendicular lean mass.

Steven B. Heymsfield · 2023 Read paper →
3D Scanning

Checker: Real-Time Scan Quality Checking and Associated User Experience

The document discusses “CHECKER,” a real-time scan quality checking system designed to enhance the user experience in mobile 3D body scanning. Developed by Size Stream, the system uses machine learning to identify and correct scan errors during the scanning process including obscured body parts, improper attire, and pose errors.

Gilmer et al. · 2023 Read paper →
3D Scanning

Improvements in Mobile 3D Body Scanning and Body Measurement

The paper aims to showcase advancements in mobile 3D body scanning and measurement technologies developed by Size Stream. These advancements focus on improving accuracy, efficiency, and user experience through innovations in machine learning, computer vision, and body reconstruction algorithms. The ultimate goal is to provide precise body measurements for applications in custom garment construction, virtual try-ons, and health and fitness monitoring.

Hauser et al. · 2023 Read paper →
3D Scanning

Mobile phone applications for 3-dimensional scanning and digital anthropometry: a precision comparison with traditional scanners

The article evaluates the precision of digital anthropometry through 3-dimensional (3D) scanning. Historical methods using large, expensive, non-portable systems has been well established. This study explores the comparative performance of modern mobile applications.

Austin J. Graybeal · 2023 Read paper →
Machine Learning

Evaluation of Automated Anthropometrics Produced by Smartphone-Based Machine Learning: A Comparison with Traditional Anthropometric Assessments

The study evaluates the accuracy and reliability of smartphone-based automated anthropometric assessments compared to traditional tape measurements. It aims to determine whether mobile applications using machine learning can provide precise estimates of waist and hip circumference (WC, HC), waist-to-hip ratio (WHR), and waist-to-height ratio (W:HT) for health assessments, especially in populations with limited access to clinical care.

Brandner et al. · 2023 Read paper →
Body Composition

Validity and Reliability of a Mobile Digital Imaging Analysis Trained by a Four-Compartment Model

The aim of this study was to assess the precision and agreement of a DIA application with developmental software trained by a 4-compartment (4C) model using an actual 4C model as the criterion method.

Brandner et al. · 2022 Read paper →
Anthropometry

Anthropometric Evaluation of a 3D Scanning Mobile Application

The study aims to compare waist, hip, upper arm, and midthigh circumference measurements acquired by a free downloadable app (MeThreeSixty; Size Stream, Cary, North Carolina) and a conventional 20-camera 3D system (SS20; Size Stream) with those measured with a flexible tape at the same anatomic sites.

Dechenaud et al. · 2022 Read paper →
Apparel & Sizing

Man vs. Machine: Measuring People for the Apparel Industry

The paper compares manual body measurements taken by skilled apparel professionals with those obtained from a Size Stream SS20 3D body scanner. The goal is to assess the reliability (precision and repeatability) and compatibility (accuracy and agreement) of these two methods. By analyzing over 60 subjects and applying statistical methods, the study aims to determine whether 3D body scanning can match or surpass traditional manual measurements in the apparel industry.

Warren P. Wright · 2019 Read paper →
Body Composition

Body F.A.T – Formulas of Adipose Tissue

This paper presents and validates new formulas for estimating human body fat content, developed by Size Stream, using data from their SS20 3D body scanner and manual measurements.

Sieglinger et al. · 2020 Read paper →
Machine Learning

Novel Body Fat Estimation Using Machine Learning and 3-Dimensional Optical Imaging

Develop and validate a new method for estimating body fat percentage (BF%) using anthropometric data obtained through 3-dimensional optical imaging (3DO) and a gold-standard 4-component (4C) body composition model.

Shepherd et al. · 2020 Read paper →
Body Composition

Size Stream Body Mass Formulas

Development of a new formula for estimating human body mass using data from Size Stream SS20 3D body scans. These formulas were developed and cross-validated using a diverse set of over 1,790 human 3D body scans (of 179 individuals). Machine learning techniques were utilized to correlate the 3D body scan data to calibrated body mass measurements.

Bruner et al. · 2019 Read paper →