Scholarlink

<p>Waist-to-hip ratio (WHR) is an essential predictor of cardiometabolic diseases, but traditional tape-based WHR measurements in children and adolescents can cause discomfort due to direct contact and are prone to measurer variation. This study aimed to develop a non-invasive, precise, and convenient alternative for WHR measurement and central obesity assessment using frequency modulated continuous wave (FMCW) radar, and to evaluate its accuracy by comparing it with traditional measurement methods. We included 100 participants aged 7–18 and radar data were analyzed using point cloud generation processed through convolutional neural networks for estimating WHR. The radar-based WHR measurements were compared to conventional clinician measurements. Participants were classified into low (WHR &lt; 0.86), moderate (≥ 0.86, &lt; 0.91) and high WHR (≥ 0.91) groups, and the classifications were compared. Strong agreement was observed between the two methods, with an intraclass correlation coefficient of 0.83 (<i>p</i> = 0.023995). The radar system achieved 82% accuracy in classifying participants into the correct abdominal obesity risk groups. Our findings demonstrate that FMCW radar can be a reliable tool for routine monitoring of central obesity. This technology addresses concerns about privacy and discomfort, making it suitable for widespread application in both clinical and non-clinical settings.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Evaluating waist-to-hip ratio in youth using frequency-modulated continuous wave radar and machine learning

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年1月31日

查看全文
  • Jun Byung Park,
  • Jinjoo Choi,
  • Jae Yoon Na,
  • Seung Hyun Kim,
  • Hyun-Kyung Park,
  • Seung Yang,
  • Sung Ho Cho

摘要

Waist-to-hip ratio (WHR) is an essential predictor of cardiometabolic diseases, but traditional tape-based WHR measurements in children and adolescents can cause discomfort due to direct contact and are prone to measurer variation. This study aimed to develop a non-invasive, precise, and convenient alternative for WHR measurement and central obesity assessment using frequency modulated continuous wave (FMCW) radar, and to evaluate its accuracy by comparing it with traditional measurement methods. We included 100 participants aged 7–18 and radar data were analyzed using point cloud generation processed through convolutional neural networks for estimating WHR. The radar-based WHR measurements were compared to conventional clinician measurements. Participants were classified into low (WHR < 0.86), moderate (≥ 0.86, < 0.91) and high WHR (≥ 0.91) groups, and the classifications were compared. Strong agreement was observed between the two methods, with an intraclass correlation coefficient of 0.83 (p = 0.023995). The radar system achieved 82% accuracy in classifying participants into the correct abdominal obesity risk groups. Our findings demonstrate that FMCW radar can be a reliable tool for routine monitoring of central obesity. This technology addresses concerns about privacy and discomfort, making it suitable for widespread application in both clinical and non-clinical settings.