Abstract
Digital microfluidic biochips (DMFBs) are increasingly important and are used for point-of-care, drug discovery, clinical diagnosis, immunoassays, etc. Pin-constrained DMFBs are an important part of digital microfluidic biochips, and they have gained increasing attention from researchers. However, many previous works have focused on the problem of electrode addressing and aimed to minimize the number of control pins in pin-constrained DMFBs. Although the number of control pins can be effectively redistributed through broadcast addressing technology, the chip reliability will be reduced if the signals are shared arbitrarily. Arbitrary signal sharing can lead to a large number of actuations for many idle electrodes, and as a result, a trapping charge or decreasing contact angle problem could occur for some electrodes, reducing the reliability of the chip. To address this problem, the appropriate electrode matching object should be carefully selected, and the influence of these factors on chip reliability should be fully considered. For this purpose, we aimed to fully consider electrode addressing and the reliability of the chip in improving the reliability of DMFBs. This paper proposed a pin addressing method based on a support vector machine (SVM) with the reliability constraint algorithm, which can fully consider the electrode addressing method and the reliability of the chip together. The proposed method achieved an average maximum number of electrode actuations that was 53.8% and 18.2% smaller than those of the baseline algorithm and the graph-based algorithm, respectively. The simulation experiment results showed that the proposed method can efficiently solve reliability problems during the DMFB design process.
Highlights
Clinical diagnosis is an important link in disease diagnosis [1]
This paper presented a novel pin addressing method based on an support vector machine (SVM) with a reliability constraint method, which can fully consider electrode addressing and the reliability of the chip together
This study investigated the design parameters, such as the number of control pins, the maximum number of electrode actuations and the CPU running time, during the Digital microfluidic biochips (DMFBs) design process
Summary
Traditional clinical disease detection usually relies on large testing equipment at a testing center, which takes a long time to detect diseases and consumes a large amount of reagents and attracts great controversy due to the need to collect many biological specimens such as blood [2]. A microfluidic chip can provide detection results in a short time by using a small number of samples, and it has a high detection sensitivity, good specificity, a simple operation process and short cycles; it has become one of the best solutions to the current problem [8]. Many traditional biological programs can be implemented efficiently in digital microfluidic systems by applying a prescheduled electrical drive sequence to control the micro-, nano- or pico-liter volume of droplets [9]. The operations can be executed anywhere on the chip by occupying a set of electrodes in a reconfigurable way
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