Utilizing Upper Arm Images in Determining Body Mass Index and Nutritional Status


  • S. F. Al-Mashaqbah Department of Biomedical Systems and Informatics Engineering, Yarmouk University, Jordan
  • W. Al-Zyoud Biomedical Engineering Dept., German Jordanian University, Amman, Jordan
  • A. Al-Zaben Department of Biomedical Systems and Informatics Engineering, Yarmouk University, Jordan
Volume: 9 | Issue: 4 | Pages: 4392-4396 | August 2019 | https://doi.org/10.48084/etasr.2858


Body mass index (BMI) is the most widely used index for determining the fitness status of an individual. Midd-upper arm circumference (MUAC) is another commonly used anthropometric index, providing a simple measurement widely used for nutrition level screening. However, building a massive population database based on both BMI and MUAC measurements is time-consuming and may introduce errors due to instrumentations and different operators. In this paper, a measurement technique of BMI from photographic images of the upper arm is presented. Three parameters are measured from the subject photos with a scale attached, and these are upper arm length, sagittal plane middle arm thickness (SMT), and frontal plane middle thickness (FMT). Different parameters are derived from the SMT and the FMT. These parameters are used to study the correlation and measurements agreements with the BMI. It is found that all parameters related to SMT correlate very well with the BMI with correlation coefficients of more than 90%. In addition, the SMT measurement limits (both upper and lower) are acceptable and within the clinical significance range. Finally, the receiver operating characteristics analysis of both SMT and MUAC has been evaluated. The findings show that SMT is slightly better than MUAC since it gives excellent sensitivity (94.7%) without compromising the specificity (88.5%) when compared to the MUAC results.


BMI, obesity, sagittal plane


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How to Cite

S. F. Al-Mashaqbah, W. Al-Zyoud, and A. Al-Zaben, “Utilizing Upper Arm Images in Determining Body Mass Index and Nutritional Status”, Eng. Technol. Appl. Sci. Res., vol. 9, no. 4, pp. 4392–4396, Aug. 2019.


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