Fluid-Dependent Single-Frequency Bioelectrical Impedance Fat Mass Estimates Compared to Digital Imaging and Dual X-ray Absorptiometry (2023)
Lexa Nescolarde , Carmine Orlandi , Gian Luca Farina, Niccolo’ Gori and Henry Lukaski
Abstract: The need for a practical method for routine determination of body fat has progressed from body mass index (BMI) to bioelectrical impedance analysis (BIA) and smartphone two-dimensional imaging. We determined agreement in fat mass (FM) estimated with 50 kHz BIA and smartphone single lateral standing digital image (SLSDI) compared to dual X-ray absorptiometry (DXA) in 188 healthy adults (69 females and 119 males). BIA underestimated (p < 0.0001) FM, whereas SLSDI FM estimates were not different from DXA values. Based on limited observations that BIA overestimated fat-free mass (FFM) in obese adults, we tested the hypothesis that expansion of the extracellular water (ECW), expressed as ECW to intracellular water (ECW/ICW), results in underestimation of BIA-dependent FM. Using a general criterion of BMI > 25 kg/m2, 54 male rugby players, compared to 40 male non-rugby players, had greater (p < 0.001) BMI and FFM but less (p < 0.001) FM and ECW/ICW. BIA underestimated (p < 0.001) FM in the non-rugby men, but SLSDI and DXA FM estimates were not different in both groups. This finding is consistent with the expansion of ECW in individuals with excess body fat due to increased adipose tissue mass and its water content. Unlike SLSDI, 50 kHz BIA predictions of FM are affected by an increased ECW/ICW associated with greater adipose tissue. These findings demonstrate the validity, practicality, and convenience of smartphone SLSDI to estimate FM, seemingly not influenced by variable hydration states, for healthcare providers in clinical and field settings.
Nutrients 2023, 15(21), 4638; https://doi.org/10.3390/nu15214638
Fluid Imbalance Clarifies Differences in Fat Estimated with Bio-Electrical Impedance Analysis Compared to Dual-Energy X-ray Absorptiometry and Single Lateral Standing Digital Image Analysis (2023)
Digital Single-Image Smartphone Assessment of Total Body Fat and Abdominal Fat Using Machine Learning (2022)
The present study demonstrates the high precision, concordance, and accuracy of a single, standing lateral 2D digital image (FYO) analyzed using automated machine learning to estimate FM in adults with a wide range of adiposity.
by Gian Luca Farina 1,*,Carmine Orlandi 2,Henry Lukaski 3 and Lexa Nescolarde 4
1 Medical Center Eubion, 00135 Rome, Italy 2 Medical Faculty, Tor Vergata University, 00133 Rome, Italy
3 Department of Kinesiology and Public Health Education, University of North Dakota, Grand Forks, ND 58202, USA
4 Department of Electronic Engineering, Universitat Politècnica de Catalunya, 08034 Barcelona, Spain
*Author to whom correspondence should be addressed. Academic Editor: James F. Rusling
Received: 2 October 2022 / Revised: 22 October 2022 / Accepted: 27 October 2022 / Published: 31 October 2022
https://www.mdpi.com/1424-8220/22/21/8365 (This article belongs to the Section Biomedical Sensors)
A Smartphone Application for Personal Assessments of Body Composition and Phenotyping (2016)
Gian Luca Farina , Fabrizio Spataro, Antonino De Lorenzo and Henry Lukaski.
Personal assessments of body phenotype can enhance success in weight management but are limited by the lack of availability of practical methods. We describe a novel smartphone application of digital photography (DP) and determine its validity to estimate fat mass (FM).
This approach utilizes the percent (%) occupancy of an individual lateral whole-body digital image and regions indicative of adipose accumulation associated with increased risk of cardio-metabolic disease. We measured 117 healthy adults (63 females and 54 males aged 19 to 65 years) with DP and dual X-ray absorptiometry (DXA) and report here the development and validation of this application.
Inter-observer variability of the determination of % occupancy was 0.02%. Predicted and reference FM values were significantly related in females (R2 = 0.949, SEE = 2.83) and males (R2 = 0.907, SEE = 2.71).
Differences between predicted and measured FM values were small (0.02 kg, p = 0.96 and 0.07 kg, p = 0.96) for females and males, respectively. No significant bias was found; limits of agreement ranged from 5.6 to 5.4 kg for females and from 5.6 to 5.7 kg for males. These promising results indicate that DP is a practical and valid method for personal body composition assessments.
A new simplified method for tracking body volume changes using digital image plethysmography (DiP)
Jordan R. Moon, Sarah E. Tobkin – Ashley A. Walter – Abbie E. Smith – Chris M. Lockwood – Travis W. Beck – Joel T. Cramer – Jeffrey R. Stout
Is Digital Image Plethysmographic (DIP) Acquisition a Valid New Tool for Preoperative Body Composition Assessment? A Validation by Dual-energy X-ray Absorptiometry (2006)
Nicola Di Lorenzo, MD, PhD, FACS – Michele Servidio, MD – Laura Di Renzo, PhD – Carmine Orlandi, PhD – Giorgio Coscarella, MD – Achille Gaspari, MD, FACS – Antonino De Lorenzo, MD, PhD
Method for estimating the fat mass of a subject through digital images
Patent number: 10460450
Abstract: A method for determining the fat mass of a subject includes the steps of acquiring an image of the subject through a digital device, and generating a virtual frame that contains at least in part that image. The virtual frame contains the subject, on the basis of its height or of the greater size in the case of animals, to provide an estimation of the content of the fat mass through an algorithm on the basis of at least an indicative index of the area occupied by the subject with respect to the area of the frame in which it is contained at least in part.
Filed: March 1, 2016
Date of Patent: October 29, 2019
Inventor: Antonio Talluri