Adaptive medical detection system: An iterative averaging method for automated detection analysis using DMFBs

In recent years a new generation of droplet based lab-on-chip device termed as Digital Microfluidic Biochip(DMFB) has found wide applications in the field of clinical diagnostics, DNA sequencing, drug design and environmental toxicity monitoring applications. Optical detection in DMFB is of major significance as it involves detection accuracy of the final results that determines the decision for clinical diagnostic solutions. In this work we propose the design of an adaptive detection system comprising of automated digital detection analyser coupled with Digital Microfluidic Biochips. The system performs automated analysis of the detection results for an obtained set of samples for the same patient and predicts the actual trend of the detection results. The technique is based on iterative averaging combined with adaptive manipulation of detection ranges determined through precharacterized values. This method provides higher detection accuracy (in the event of uncertainty resulted when no clear detection majority is available) with an approximated prediction of the trend of the extent of infection or abnormality of the targeted parameter. The design is simulated in FPGA platform and the detection results display fair amount of accuracy particularly in line with conventional laboratory methods.