Ensuring the operational health of droplet-based microelectrofluidic biosensor systems

Recent events have heightened the need for fast, accurate, and reliable biological/chemical sensor systems for critical locations. As droplet-based microelectrofluidic sensor systems become widespread in these safety-critical biomedical applications, reliability emerges as a critical performance parameter. In order to ensure the operational health of such safety-critical systems, they need to be monitored for defects, not only after manufacturing, but also during in-field operation. In this paper, we present a cost-effective concurrent test methodology for droplet-based microelectrofluidic systems. We present a classification of catastrophic and parametric faults in such systems and show how faults can be detected by electrostatically controlling and tracking droplet motion. We then present a fault simulation approach based on tolerance analysis using Monte-Carlo simulation to characterize the impact of parameter variations on system performance. Finally, we present experimental results on a droplet-based microelectrofluidic system for a real-time polymerase chain reaction application.