AI-Based Detection of Droplets and Bubbles in Digital Microfluidic Biochips

Jianan Xu, Wenjie Fan, Jan Madsen, Georgi Plamenov Tanev, Luca Pezzarossa

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review


Digital microfluidic biochips exploit the electrowet-ting on dielectric effect to move and manipulate microliter-sized liquid droplets on a planar surface. This technology has the potential to automate and miniaturize biochemical processes, but reliability is often an issue. The droplets may get temporarily stuck or gas bubbles may impede their movement leading to a disruption of the process being executed. However, if the position and size of the droplets and bubbles are known at run-time, these undesired effects can be easily mitigated by the biochip control system. This paper presents an AI-based computer vision solution for real-time detection of droplets and bubbles in DMF biochips and its implementation that supports cloud-based deployment. The detection is based on the YOLOv5 framework in combination with custom pre and post-processing techniques. The YOLOv5 neural network is trained using our own data set consisting of 5115 images. The solution is able to detect droplets and bubbles with real-time speed and high accuracy and to differentiate between them even in the extreme case where bubbles coexist with transparent droplets.
Original languageEnglish
Title of host publicationProceedings of the 2023 Design, Automation & Test in Europe Conference & Exhibition (DATE)
Number of pages6
Publication date2023
Article number10136887
ISBN (Print)979-8-3503-9624-9
Publication statusPublished - 2023
Event2023 Design, Automation and Test in Europe Conference and Exhibition - Antwerp, Belgium
Duration: 17 Apr 202319 Apr 2023
Conference number: 26


Conference2023 Design, Automation and Test in Europe Conference and Exhibition


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