Testing Path Searching for Digital Microfluidic Biochips based on the Improved Particle Swarm Optimization

Abstract

Digital microfluidic biochips (DMFBs) is an attractive platform for immunoassays, point-of-care clinical diagnostics due to its flexible application and low fabrication cost and further for the development of instruments. Due to the DMFBs have been applied for these safe-critical field, those procedures require high output precision, so the reliability of the chips are extremely important. On-line testing methods are required to ensure robust DMFB operation and high confidence in the outcome of experiments, so a robust testing method is necessary. Many testing methods have been proposed, but most of them are simple functional testing or off-line testing. These testing methods are increasingly unable to meet the requirements of current chip testing. The online test means that there are testing droplet and bioassays running on the DMFB simultaneously. This paper introduces a heuristic method to optimize the testing path. The study utilizes the improved particle swarm optimization to solve the problem. The simulation results showed the proposed method is convergent and could be applied in various operations to reduce about 20% searching time, compared with the improved ant colony algorithm.