Error recovery in a micro-electrode-dot-array digital microfluidic biochip?

Published

Conference Paper

© 2016 ACM. A digital microfluidic biochip (DMFB) is an attractive technology platform for automating laboratory procedures in biochemistry. However, today's DMFBs suffer from several limitations: (i) constraints on droplet size and the inability to vary droplet volume in a fine-grained manner; (ii) the lack of integrated sensors for real-time detection; (iii) the need for special fabrication processes and the associated reliability/yield concerns. To overcome the above problems, DMFBs based on a micro-electrode-dot-array (MEDA) architecture have been proposed recently, and droplet manipulation on these devices has been experimentally demonstrated. Errors are likely to occur due to defects, chip degradation, and the lack of precision inherent in biochemical experiments. Therefore, an efficient error-recovery strategy is essential to ensure the correctness of assays executed on MEDA biochips. By exploiting MEDA-specific advances in droplet sensing, we present a novel error-recovery technique to dynamically reconfigure the biochip using real-time data provided by on-chip sensors. Local recovery strategies based on probabilistic-timed-automata are presented for various types of errors. A control flow is also proposed to connect local recovery procedures with global error recovery for the complete bioassay. Laboratory experiments using a fabricated MEDA chip are used to characterize the outcomes of key droplet operations. The PRISM model checker and three analytical chemistry benchmarks are used for an extensive set of simulations. Our results highlight the effectiveness of the proposed error-recovery strategy.

Full Text

Duke Authors

Cited Authors

  • Li, Z; Lai, KYT; Yu, PH; Chakrabarty, K; Pajic, M; Ho, TY; Lee, CY

Published Date

  • November 7, 2016

Published In

Volume / Issue

  • 07-10-November-2016 /

International Standard Serial Number (ISSN)

  • 1092-3152

International Standard Book Number 13 (ISBN-13)

  • 9781450344661

Digital Object Identifier (DOI)

  • 10.1145/2966986.2967035

Citation Source

  • Scopus