Multiple fault diagnosis in digital microfluidic biochips

  • Authors:
  • Daniel Davids;Siddhartha Datta;Arindam Mukherjee;Bharat Joshi;Arun Ravindran

  • Affiliations:
  • University of North Carolina, Charlotte, NC;University of North Carolina, Charlotte, NC;University of North Carolina, Charlotte, NC;University of North Carolina, Charlotte, NC;University of North Carolina, Charlotte, NC

  • Venue:
  • ACM Journal on Emerging Technologies in Computing Systems (JETC)
  • Year:
  • 2006

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Abstract

Microfluidics-based biochips consist of microfluidic arrays on rigid substrates through which, movement of fluids is tightly controlled to facilitate biological reactions. Biochips are soon expected to revolutionize biosensing, clinical diagnostics, and drug discovery. Critical to the deployment of biochips in such diverse areas is the dependability of these systems. Thus, robust testing techniques are required to ensure an adequate level of system dependability. Due to the underlying mixed technology and energy domains, such biochips exhibit unique failure mechanisms and defects. In this article we present a highly effective fault diagnosis strategy that uses a single source and sink to detect and locate multiple faults in a microfluidic array, without flooding the array, a problem that has hampered realistic implementations of all existing strategies. The strategy renders itself well for a built-in self-test that could drastically reduce the operating cost of microfluidic biochips. It can be used during both the manufacturing phase of the biochip, as well as field operation. Furthermore, the algorithm can pinpoint the actual fault, as opposed to merely the faulty regions that are typically identified by strategies proposed in the literature. Also, analytical results suggest that it is an effective strategy that can be used to design highly dependable biochip systems.