Automated Flow Tracking Software for Capillary Microfluidic Devices

This paper introduces an automated flow-tracking software for capillaric microfluidic devices, that use capillary action to drive flow without external pumps. Tracking liquid menisci in such devices is important for analysing flow rates, surface treatment efficacy, and valve efficacy. Traditional object-tracking methods have limitations when applied to microfluidic environments, especially due to the small scale, slow speeds, and shape changes of the meniscus. The proposed software uses image processing techniques and OpenCV's channel and spacial reliability (CSRT) object tracker to accurately track flow velocity within microfluidic devices, overcoming challenges presented by transparency and directional changes. Experimental results demonstrate the effectiveness of the tool compared to manual tracking, showing its potential for enhancing accuracy while reducing labour-intensive manual processing steps. Further improvements, such as multi-flow tracking and machine learning integration, are suggested for future work.