Adaptive error recovery in MEDA biochips based on droplet-aliquot operations and predictive analysis

Published

Conference Paper

© 2017 IEEE. Digital microfluidic biochips (DMFBs) are being increasingly used in biochemistry labs for automating bioassays. However, traditional DMFBs suffer from some key shortcomings: 1) inability to vary droplet volume in a flexible manner; 2) difficulty of integrating on-chip sensors; 3) the need for special fabrication processes. To overcome these problems, DMFBs based on micro-electrode-dot-array (MEDA) have recently be-en proposed. However, errors are likely to occur on a MEDA DMFB due to chip defects and the unpredictability inherent to biochemical experiments. We present fine-grained error-recovery solutions for MEDA by exploiting real-time sensing and advanced MEDA-specific droplet operations. The proposed methods rely on adaptive droplet-aliquot operations and predictive analysis of mixing. Experimental results on three representative benchmarks demonstrate the efficiency of the proposed error-recovery strategy.

Full Text

Duke Authors

Cited Authors

  • Zhong, Z; Li, Z; Chakrabarty, K

Published Date

  • December 13, 2017

Published In

Volume / Issue

  • 2017-November /

Start / End Page

  • 615 - 622

International Standard Serial Number (ISSN)

  • 1092-3152

International Standard Book Number 13 (ISBN-13)

  • 9781538630938

Digital Object Identifier (DOI)

  • 10.1109/ICCAD.2017.8203834

Citation Source

  • Scopus