Batista Luna Taira, García Bello Jose Luis, Lara Lafargue Alcibíades, Camué Ciria Héctor Manuel, Zulueta Yohandys A
Autonomous University of Santo Domingo (UASD), UASD Nagua Center, Dominican Republic.
Autonomous University of Santo Domingo (UASD), San Francisco de Macorís Campus, Dominican Republic.
J Electr Bioimpedance. 2025 May 26;16(1):62-68. doi: 10.2478/joeb-2025-0009. eCollection 2025 Jan.
In this study, a linear support vector machine regression model was used to explore the correlation between weight status and two novel bioparameters, specific resistance and reactance, in an infant-juvenile cohort from eastern Cuba. The model was trained using various characteristics, including bioimpedance measurements, to predict phase angle, specific resistance, and reactance with high accuracy. The results showed that the variation of these characteristics with weight status and sex is consistent with previous literature. Additionally, two robust bioparameters derived from bioimpedance measurements and anthropometric-physiological parameters were identified for predicting weight status. The predictive models developed in this study are essential for accurately assessing weight status and disease risks in infants and juveniles in the eastern Cuban region. These findings highlight the potential applications of bioimpedance measurements and bioparameters in health and disease risk assessment, contributing to the growing body of literature on this topic.
在本研究中，使用线性支持向量机回归模型，在来自古巴东部的婴幼儿队列中，探究体重状况与两个新生物参数（比电阻和电抗）之间的相关性。该模型利用包括生物电阻抗测量在内的各种特征进行训练，以高精度预测相角、比电阻和电抗。结果表明，这些特征随体重状况和性别的变化与先前文献一致。此外，还确定了两个从生物电阻抗测量和人体测量 - 生理参数得出的稳健生物参数，用于预测体重状况。本研究中开发的预测模型对于准确评估古巴东部地区婴幼儿的体重状况和疾病风险至关重要。这些发现突出了生物电阻抗测量和生物参数在健康和疾病风险评估中的潜在应用，为该主题的文献不断增加做出了贡献。
