NEWS ARTICLE
学术动态：PSAML: A Methodological Approach for Noninvasive Computerized Hydration Level Estimation
论文标题：PSAML: A Methodological Approach for Noninvasive Computerized Hydration Level Estimation
发布日期：2026-05-26
作者：Xin Liu, Xuezhao Kang, Liqun He, Jianrui Zhang, Huyan Ting
DOI：10.3390/s26113362
论文摘要：Hydration level (HL) is a critical physiological indicator of human health and functional status, and accurate HL monitoring is essential for applications in healthcare, sports, and wellness assessment. However, existing methods are either invasive and inconvenient or noninvasive but limited by system complexity and insufficient accuracy. To address these limitations, this study proposes a methodological approach for noninvasive computerized HL estimation based on galvanic skin response (GSR) signals, termed the PSAML approach, which integrates principal component analysis (PCA), successive decomposition index (SDI), and machine learning (ML) classifiers. A representative GSR dataset was collected from three healthy subjects under dehydrated, normal, and overhydrated states in sitting, standing, and posture-independent scenarios. After preprocessing, including outlier removal, Butterworth filtering, and time-window segmentation, conventional time-domain features were extracted and compared with PCA- and SDI-based representations. Six ML algorithms were used for classification. The results show that the conventional feature method achieved a maximum accuracy of 63.97%, whereas PCA-based feature reduction significantly improved performance, with PCA+SVM, PCA+LR, and PCA+LDA achieving accuracies above 99% in most cases. SDI-based features also demonstrated strong performance with suitable classifiers under smaller time windows. These findings demonstrate that the proposed PSAML approach provides an accurate and efficient solution for wearable noninvasive HL monitoring.
元数据：Crossref 收录的 MDPI Sensors 论文。 DOI: 10.3390/s26113362. Vol. 26, Issue 11. Authors: Xin Liu, Xuezhao Kang, Liqun He, Jianrui Zhang, Huyan Ting.
开放许可：https://creativecommons.org/licenses/by/4.0/
原文链接：https://doi.org/10.3390/s26113362
PDF 链接：https://www.mdpi.com/1424-8220/26/11/3362/pdf