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Comparing the accuracy of ES-BC, EIS-GS, and ES Oxi on body composition, autonomic nervous system activity, and cardiac output to standardized assessments

Authors Lewis J, Tannenbaum SL, Gao J, Melillo AB, Long EG, Alonso Y, Konefal J, Woolger JM, Leonard S, Singh PK, Chen L, Tiozzo E

Published 16 September 2011 Volume 2011:4 Pages 169—177

DOI https://doi.org/10.2147/MDER.S24291

Review by Single-blind

Peer reviewer comments 2

John E Lewis1, Stacey L Tannenbaum1, Jinrun Gao3, Angelica B Melillo1, Evan G Long1, Yaima Alonso2, Janet Konefal1, Judi M Woolger2, Susanna Leonard1, Prabjot K Singh1, Lawrence Chen1, Eduard Tiozzo1
1Department of Psychiatry and Behavioral Sciences, 2Department of Medicine, University of Miami Miller School of Medicine, Miami, FL, 3State Farm Insurance, Bloomington, IL, USA

Background and purpose: The Electro Sensor Complex (ESC) is software that combines three devices using bioelectrical impedance, galvanic skin response, and spectrophotometry: (1) ES-BC (Electro Sensor-Body Composition; LD Technology, Miami, FL) to assess body composition, (2) EIS-GS (Electro Interstitial Scan-Galvanic Skin; LD Technology) to predict autonomic nervous system activity, and (3) ES Oxi (Electro Sensor Oxi; LD Technology) to assess cardiac output. The objective of this study was to compare each to a standardized assessment: ES-BC to dual-energy X-ray absorptiometry (DXA), EIS-GS to heart rate variability, and ES Oxi to BioZ Dx Diagnostic System (BioZ Dx; SonoSite Inc, Bothell, WA).
Patients and methods: The study was conducted in two waves. Fifty subjects were assessed for body composition and autonomic nervous system activity. Fifty-one subjects were assessed for cardiac output.
Results: We found adequate relative and absolute agreement between ES-BC and DXA for fat mass (r = 0.97, P < 0.001) with ES-BC overestimating fat mass by 0.1 kg and for body fat percentage (r = 0.92, P < 0.001) with overestimation of fat percentage by 0.4%. For autonomic nervous system activity, we found marginal relative agreement between EIS-GS and heart rate variability by using EIS-GS as the predictor in a linear regression equation (adjusted R2 = 0.56, P = 0.03). For cardiac output, adequate relative and absolute agreement was found between ES Oxi and BioZ Dx at baseline (r = 0.60, P < 0.001), after the first exercise stage (r = 0.79, P < 0.001), and after the second exercise stage (r = 0.86, P < 0.001). Absolute agreement was found at baseline and after both bouts of exercise; ES Oxi overestimated baseline and stage 1 exercise cardiac output by 0.3 L/minute and 0.1 L/minute, respectively, but exactly estimated stage 2 exercise cardiac output.
Conclusion: ES-BC and ES Oxi accurately assessed body composition and cardiac output compared to standardized instruments, whereas EIS-GS showed marginal predictive ability for autonomic nervous system activity. The ESC software managing the three devices would be useful to help detect complications related to metabolic syndrome, diabetes, and cardiovascular disease and to noninvasively and rapidly manage treatment follow-up.

Keywords: fat mass, autonomic nervous system activity, Electro Sensor Complex, dual-energy X-ray absorptiometry, heart rate variability, and bioimpedance cardiography

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