Choi, Ahyoung; Kim, Justin Younghyun; Jo, Seongwook; Jee, Jae Hwan; Heymsfield, Steven B; Bhagat, Yusuf A; Kim, Insoo; Cho, Jaegeol
Sensors (Basel, Switzerland)
2015NA ; 15 ( 9 ) :22151-66.
PMID : 26364636
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Choi, Ahyoung - DMC R&D Center, Samsung Electronics, Suwon 16677, Gyeonggi, Korea. ay12.choi@samsung.com.
Kim, Justin Younghyun - DMC R&D Center, Samsung Electronics, Suwon 16677, Gyeonggi, Korea. vine.kim@samsung.com.
Jo, Seongwook - DMC R&D Center, Samsung Electronics, Suwon 16677, Gyeonggi, Korea. sw0326.jo@samsung.com.
Jee, Jae Hwan - Center for Health Promotion, Samsung Medical Center, Seoul 06351, Korea. jaehwan.jee@samsung.com.
Heymsfield, Steven B - Pennington Biomedical Research Center, Baton Rouge, LA 70808, USA. steven.heymsfield@pbrc.edu.
Bhagat, Yusuf A - Samsung Research America, Richardson, TX 75082, USA. y.bhagat@samsung.com.
Kim, Insoo - Samsung Research America, Richardson, TX 75082, USA. insoo3.kim@samsung.com.
Cho, Jaegeol - DMC R&D Center, Samsung Electronics, Suwon 16677, Gyeonggi, Korea. jgirlcho@samsung.com.
ABSTRACT
Current bioelectric impedance analysis (BIA) systems are often large, cumbersome devices which require strict electrode placement on the user, thus inhibiting mobile capabilities. In this work, we developed a handheld BIA device that measures impedance from multiple frequencies (5 kHz~200 kHz) with four contact electrodes and evaluated the BIA device against standard body composition analysis systems: a dual-energy X-ray absorptiometry (DXA) system (GE Lunar Prodigy, GE Healthcare, Buckinghamshire, UK) and a whole-body BIA system (InBody S10, InBody, Co. Ltd, Seoul, Korea). In the study, 568 healthy participants, varying widely in body mass index, age, and gender, were recruited at two research centers: the Samsung Medical Center (SMC) in South Korea and the Pennington Biomedical Research Center (PBRC) in the United States. From the measured impedance data, we analyzed individual body fat and skeletal muscle mass by applying linear regression analysis against target reference data. Results indicated strong correlations of impedance measurements between the prototype pathways and corresponding InBody S10 electrical pathways (R = 0.93, p < 0.0001). Additionally, body fat estimates from DXA did not yield significant differences (p > 0.728 (paired t-test), DXA mean body fat 29.45 ± 10.77 kg, estimated body fat 29.52 ± 12.53 kg). Thus, this portable BIA system shows a promising ability to estimate an individual's body composition that is comparable to large stationary BIA systems.
keyword
body composition analysis; mobile health; obesity management
MESH
Adult, Anthropometry/*instrumentation/methods, Body Composition/*physiology, Electric Impedance/*therapeutic use, Equipment Design, Female, Humans, Male, Middle Aged, Obesity/*therapy, Regression Analysis, *Smartphone, Software, Telemedicine/*instrumentation
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