.png){kind=icon}
返回
Miniaturized multispectral imaging for microfluidic pH sensing
.png){kind=icon}
OA
AI
DOI：10.1016/j.sbsr.2025.100764.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Multispectral lab-on-chip imaging based on complementary metal-oxide semiconductor (CMOS) is an innovative technology that supports portable microfluidic platforms and enables the extraction of spectral information from specimens under multiple wavelengths. Accurate pH sensing is essential across a diverse range of chemical, biological, medical, and environmental applications. In this paper, we presented a new approach for pH sensing using the CMOS-based multispectral lab-on-chip imaging. Using a six-band color filter array that spans the optical spectrum in the visible and near-infrared range and a U-shape PDMS microfluidic channel, images of solutions with specific pH values were captured by a monochrome CMOS image sensor. To predict pH values, we developed a Support Vector Regression (SVR) model, which was trained using captured images of the six bands. Predicted pH values were obtained by the model with an RMSE of 0.364. Our research demonstrates that multispectral lab-on-chip imaging represents a miniature and rapid method to achieve pH sensing with high sensitivity and accuracy.
Keyword:
Lab-on-chip
Multispectral imaging
Microfluidic
pH sensing
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
4.9
论文数:
768
被引数:
2.6K
机构
引用论文
Holographic Image Reconstruction with Phase Recovery and Autofocusing Using Recurrent Neural Networks.png)
ACS PHOTONICSOAAI
ACS PHOTONICSIF6.7
OAAI分享收藏Evaluation of water quality indexes with novel machine learning and SHapley Additive ExPlanation (SHAP) approaches使用新颖的机器学习和SHapley加法解释 (SHAP) 方法评估水质指标
PREAI
分享收藏Toward Electrically Tunable, Lithography-Free, Ultra-Thin Color Filters Covering the Whole Visible SpectrumSCIENTIFIC REPORTSOAAI
SCIENTIFIC REPORTSIF3.9
OAAI分享收藏Explanation of machine learning models using shapley additive explanation and application for real data in hospital基于shapley可加性的机器学习模型解释及其在医院实际数据中的应用OAAI
OAAI分享收藏
查看更多内容