文献类型：期刊文献

英文题名：Intelligent droplet tracking with correlation filters for digital microfluidics

作者：Li, Libin[1];Gu, Zhen[1];Zhou, Jia-Le[1];Yan, Bingyong[1];Kong, Cong[2];Wang, Hua[3];Wang, Hui-Feng[1]

机构：[1]East China Univ Sci & Technol, Minist Educ, Key Lab Adv Control & Optimizat Chem Proc, Shanghai 200237, Peoples R China;[2]Chinese Acad Fishery Sci, East China Sea Fisheries Res Inst, Key Lab East China Sea Fishery Resources Exploita, Minist Agr & Rural Affairs, Shanghai 200090, Peoples R China;[3]Shanghai Jiao Tong Univ, Renji Hosp, Sch Med, Dept Lab Med, Shanghai 200137, Peoples R China

年份：2021

卷号：32

期号：11

起止页码：3416

外文期刊名：CHINESE CHEMICAL LETTERS

收录：;WOS:【SCI-EXPANDED(收录号:WOS:000732588900021)】；

基金：The authors would like to thank the financial support from the National Natural Science Foundation of China (Nos. 31701698, 81972017), Shanghai Key Laboratory of Forensic Medicine, Academy of Forensic Science (No. KF1910) and Shanghai Shenkang Hospital Development Center to promote clinical skills and clinical innovation ability in municipal hospitals of the Three-year Action Plan Project (No. SHDC2020CR3006A)

语种：英文

外文关键词：Digital microfluidics; Correlation filter trackers; Machine vision; Reaction kinetics; Colorimetric assay

摘要：Tracking the movement of droplets in digital microfluidics is essential to improve its control stability and obtain dynamic information for its applications such as point-of-care testing, environment monitoring and chemical synthesis. Herein, an intelligent, accurate and fast droplet tracking method based on machine vision is developed for applications of digital microfluidics. To continuously recognize the transparent droplets in real-time and avoid the interferes from background patterns or inhomogeneous illumination, we introduced the correlation filter tracker, enabling online learning of the multi-features of the droplets in Fourier domain. Results show the proposed droplet tracking method could accurately locate the droplets. We also demonstrated the capacity of the proposed method for estimation of the droplet velocity as faster as 20 mm/s, and its application in online monitoring the Griess reaction for both colorimetric assay of nitrite and study of reaction kinetics. (C) 2021 Published by Elsevier B.V. on behalf of Chinese Chemical Society and Institute of Materia Medica, Chinese Academy of Medical Sciences.