Suppr超能文献

用于慢性肾脏病长期尿液监测的基于智能手机的比色校正分析系统。

Smartphone-based colorimetric correction analysis system for long-term urine monitoring of chronic kidney disease.

作者信息

Xu Hong, Hua Yiran, Li Haiqin, Wang Jianhua, Liu Gaohong, Li Xiaochun

机构信息

Institute of Biomedical Precision Testing and Instrumentation, College of Artificial Intelligence, Taiyuan University of Technology, Jinzhong, Shanxi, 030600, China.

Institute of Biomedical Precision Testing and Instrumentation, College of Artificial Intelligence, Taiyuan University of Technology, Jinzhong, Shanxi, 030600, China.

出版信息

Anal Biochem. 2025 Jul;702:115824. doi: 10.1016/j.ab.2025.115824. Epub 2025 Feb 28.

Abstract

The chronic kidney disease (CKD) poses a serious threat to human health. Long-term monitoring of urine is important in the management of CKD. Currently, the accuracy and stability of smartphone-based colorimetric analysis of urine indicators are limited due to the impact of different image-taking conditions on captured digital images of urine test strips. Herein, an attachment-free colorimetric correction analysis system (CCAS for short), consisting of a self-designed urine test strip array and an Android application integrated with an image calibration algorithm, were proposed for quantitative analysis of nine urine indicators. With this system the impact of image-taking conditions on captured digital image were largely corrected, and thus the accuracy and stability for digital image colorimetric analysis of urine test strip were improved. The limits of detection of creatinine, nitrite, urinary calcium, microalbumin, bilirubin, protein, pH, haemoglobin, and glucose were 1.607 mmol/L, 1.232 μmol/L, 0.297 mmol/L, 11.116 mg/L, 1.155 μmol/L, 0.042 g/L, 0.044, 0.058 mg/L, and 0.122 mmol/L, respectively. The accuracy of CCAS was validated by analyzing artificial urine samples and 143 clinical urine samples. As an accurate, low-cost and reliable system, CCAS addresses specific needs for patients to monitor their urine whenever and wherever possible with only their own smartphone.

摘要

慢性肾脏病(CKD)对人类健康构成严重威胁。长期监测尿液对CKD的管理很重要。目前,由于不同的图像采集条件对尿液试纸条采集的数字图像有影响,基于智能手机的尿液指标比色分析的准确性和稳定性受到限制。在此,提出了一种无附件比色校正分析系统(简称为CCAS),该系统由自行设计的尿液试纸条阵列和集成了图像校准算法的安卓应用程序组成,用于对九种尿液指标进行定量分析。通过该系统,很大程度上校正了图像采集条件对采集的数字图像的影响,从而提高了尿液试纸条数字图像比色分析的准确性和稳定性。肌酐、亚硝酸盐、尿钙、微量白蛋白、胆红素、蛋白质、pH值、血红蛋白和葡萄糖的检测限分别为1.607 mmol/L、1.232 μmol/L、0.297 mmol/L、11.116 mg/L、1.155 μmol/L、0.042 g/L、0.044、0.058 mg/L和0.122 mmol/L。通过分析人工尿液样本和143份临床尿液样本验证了CCAS的准确性。作为一种准确、低成本且可靠的系统,CCAS满足了患者随时随地仅用自己的智能手机监测尿液的特定需求。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验