SVM-based waist circumference estimation using Kinect.

Journal: Computer methods and programs in biomedicine
PMID: 32126448

Abstract

BACKGROUND AND OBJECTIVE: Conventional anthropometric studies using Kinect depth sensors have concentrated on estimating the distances between two points such as height. This paper deals with a novel waist measurement method using SVM regression, further widening spectrum of Kinect's potential applications. Waist circumference is a key index for the diagnosis of abdominal obesity, which has been linked to metabolic syndromes and other related diseases. Yet, the existing measuring method, tape measure, requires a trained personnel and is therefore costly and time-consuming.

Authors

  • Dasom Seo
    Division of Computer Science and Engineering, Jeonbuk National University, Jeonju, Republic of Korea. Electronic address: ssomncandy@gmail.com.
  • Euncheol Kang
    Division of Computer Science and Engineering, Jeonbuk National University, Jeonju, Republic of Korea. Electronic address: ec.kang@jbnu.ac.kr.
  • Yu-Mi Kim
    Center for Clinical Pharmacology and Biomedical Research Institute, Jeonbuk National University Hospital, Jeonju, Republic of Korea; Department of Pharmacology, School of Medicine, Jeonbuk National University, Jeonju, Republic of Korea. Electronic address: nagaya0010@gmail.com.
  • Sun-Young Kim
    Graduate School of Cancer Science and Policy, National Cancer Center, Gyeonggi, South Korea.
  • Il-Seok Oh
    Division of Computer Science and Engineering, Chonbuk National University, 567 Baekje-daero, Deokjin-gu, Jeonju-si 54896, Republic of Korea.
  • Min-Gul Kim
    Center for Clinical Pharmacology and Biomedical Research Institute, Jeonbuk National University Hospital, Jeonju, Republic of Korea; Research Institute of Clinical Medicine of Jeonbuk National University, Jeonju, Republic of Korea; Department of Pharmacology, School of Medicine, Jeonbuk National University, Jeonju, Republic of Korea. Electronic address: mgkim@jbnu.ac.kr.

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