Test Diagnosis of Digital Microfluidic Biochips Using Image Segmentation

Abstract

Digital microfluidic biochip has been developed as a promising alternative to the traditional approach of benchtop biochemical laboratory tests. Dependability is an important attribute for microfluidic biochips that are used for safety-critical applications, such as point-of-care health assessment, air-quality monitoring, and food-safety testing. Therefore, the robust offline and online test techniques are required after manufacturing and during bioassay operations. In this work, we are presenting an image segmentation based testing methodology to detect the catastrophic faults and to locate the faulty cells. The design-for diagnosability scheme is proposed, and it is shown that faults can be located and tolerated by providing alternative paths in biochips. Moreover this testing method also facilitates the testing of a biochip with other bioassay operations running concurrently.