title: Regression models for near-infrared measurement of subcutaneous adipose tissue thickness.
abstract: Obesity is often associated with the risks of diabetes and cardiovascular disease, and there is a need to measure subcutaneous adipose tissue (SAT) thickness for acquiring the distribution of body fat. The present study aimed to develop and evaluate different model-based methods for SAT thickness measurement using an SATmeter developed in our laboratory. Near-infrared signals backscattered from the body surfaces from 40 subjects at 20 body sites each were recorded. Linear regression (LR) and support vector regression (SVR) models were established to predict SAT thickness on different body sites. The measurement accuracy was evaluated by ultrasound, and compared with results from a mechanical skinfold caliper (MSC) and a body composition balance monitor (BCBM). The results showed that both LR- and SVR-based measurement produced better accuracy than MSC and BCBM. It was also concluded that by using regression models specifically designed for certain parts of human body, higher measurement accuracy could be achieved than using a general model for the whole body. Our results demonstrated that the SATmeter is a feasible method, which can be applied at home and in the community due to its portability and convenience.
authors.affiliation: College of Life Science and Bioengineering, Beijing University of Technology, Beijing 100124, People's Republic of China. China-Japan Friendship Hospital, Beijing 100029, People's Republic of China.
authors.forename: Yu
authors.initials: Y
authors.lastname: Wang
authors.forename: Dongmei
authors.initials: D
authors.lastname: Hao
authors.forename: Jingbin
authors.initials: J
authors.lastname: Shi
authors.forename: Zeqiang
authors.initials: Z
authors.lastname: Yang
authors.forename: Liu
authors.initials: L
authors.lastname: Jin
authors.forename: Song
authors.initials: S
authors.lastname: Zhang
authors.forename: Yimin
authors.initials: Y
authors.lastname: Yang
authors.forename: Guangyu
authors.initials: G
authors.lastname: Bin
authors.forename: Yanjun
authors.initials: Y
authors.lastname: Zeng
authors.forename: Dingchang
authors.initials: D
authors.lastname: Zheng
mesh_terms: D015992:Body Mass Index; D004867:Equipment Design; D005240:Feasibility Studies; D005260:Female; D006801:Humans; D007259:Infrared Rays; D008297:Male; D008954:Models, Biological; D009765:Obesity / Q000000981:diagnostic imaging; D061848:Optical Imaging / Q000295:instrumentation / Q000379:methods*; D012044:Regression Analysis; D012542:Scattering, Radiation; D012885:Skinfold Thickness; D050151:Subcutaneous Fat / Q000000981:diagnostic imaging*; D060388:Support Vector Machine; D055815:Young Adult