Automated Calculation of Height and Area of Human Body for Estimating Body Weight Using a Matlab-based Kinect Camera

IF 2.4 Q2 MULTIDISCIPLINARY SCIENCES

Smart Science Pub Date : 2021-11-02 DOI:10.1080/23080477.2021.1983940

A. Naufal, C. Anam, C. E. Widodo, G. Dougherty

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引用次数: 4

Abstract

ABSTRACT Body size is an important parameter in radiology examinations. Measurements of body size may be carried out remotely using a Kinect camera. We aim to develop a Matlab-based software that can be used to automatically measure the height and area in order to estimate the weight of a human body without direct contact. The size and depth of the image were calibrated for various object-Kinect distances. The depth image was segmented and normalized into a binary image, from which the height and area were calculated. The height and area of the body were correlated with the body weight. We analyzed the images obtained from 147 participants aged 5–70 years old and weighing 13.7–89.9 kg. The height measured using the Kinect camera had a high correlation with a ruler with R2 = 0.96 (p = 0.0096), and error percentage of 1.04%. It is also found that the height and area of the participants are well correlated with the weight of the participants with R2 of 0.453 and 0.658, respectively. A graphical user interface for automatically calculating the height and area of the human body has been successfully developed. GRAPHICAL ABSTRACT

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基于Matlab的运动相机自动计算人体高度和面积以估计体重

体尺寸是放射学检查中的一个重要参数。可以使用Kinect摄像头远程测量身体尺寸。我们的目标是开发一个基于matlab的软件，可以自动测量高度和面积，以便在没有直接接触的情况下估计人体的重量。图像的大小和深度根据不同的物体- kinect距离进行校准。对深度图像进行分割并归一化为二值图像，计算深度图像的高度和面积。体高、体面积与体重呈正相关。我们分析了147名年龄在5-70岁，体重13.7-89.9 kg的参与者的图像。使用Kinect相机测量的身高与尺子的高度相关，R2 = 0.96 (p = 0.0096)，错误率为1.04%。研究还发现，参与者的身高和面积与参与者的体重有很好的相关关系，R2分别为0.453和0.658。成功地开发了一个用于自动计算人体高度和面积的图形用户界面。图形抽象

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来源期刊

Smart Science Engineering-Engineering (all)

CiteScore

4.70

自引率

4.30%

发文量

期刊介绍： Smart Science (ISSN 2308-0477) is an international, peer-reviewed journal that publishes significant original scientific researches, and reviews and analyses of current research and science policy. We welcome submissions of high quality papers from all fields of science and from any source. Articles of an interdisciplinary nature are particularly welcomed. Smart Science aims to be among the top multidisciplinary journals covering a broad spectrum of smart topics in the fields of materials science, chemistry, physics, engineering, medicine, and biology. Smart Science is currently focusing on the topics of Smart Manufacturing (CPS, IoT and AI) for Industry 4.0, Smart Energy and Smart Chemistry and Materials. Other specific research areas covered by the journal include, but are not limited to: 1. Smart Science in the Future 2. Smart Manufacturing: -Cyber-Physical System (CPS) -Internet of Things (IoT) and Internet of Brain (IoB) -Artificial Intelligence -Smart Computing -Smart Design/Machine -Smart Sensing -Smart Information and Networks 3. Smart Energy and Thermal/Fluidic Science 4. Smart Chemistry and Materials