Skip to main content
SpringerLink
Log in

Efficient and Adaptive Error Recovery

  • Chapter
  • First Online:
Micro-Electrode-Dot-Array Digital Microfluidic Biochips

  • 345 Accesses

Abstract

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 micro-electrode-dot-array (MEDA) biochips. By exploiting MEDA-specific advances in droplet sensing, this chapter presents 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. An online synthesis technique and a control flow are also proposed to connect local-recovery procedures with global error recovery for the complete bioassay. Moreover, an integer linear programming-based method is also proposed to select the optimal local-recovery time for each operation. Laboratory experiments using a fabricated MEDA chip are used to characterize the outcomes of key droplet operations. The PRISM model checker and three benchmarks are used for an extensive set of simulations. Our results highlight the effectiveness of the proposed error-recovery strategy.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
eBook
USD 16.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Li, Z., Lai, K. Y.-T., Yu, P.-H., Chakrabarty, K., Pajic, M., Ho, T.-Y., et al. (2016). Error recovery in a micro-electrode-dot-array digital microfluidic biochip. In Proceedings of IEEE/ACM International Conference on Computer-Aided Design, pp. 105:1–105:8.

    Google Scholar 

  2. Jaress, C., Brisk, P., & Grissom, D. (2015). Rapid online fault recovery for cyber-physical digital microfluidic biochips. In Proceedings of IEEE VLSI Test Symposium, pp. 1–6.

    Google Scholar 

  3. Zhao, Y., Xu, T., & Chakrabarty, K. (2010). Integrated control-path design and error recovery in the synthesis of digital microfluidic lab-on-chip. ACM Journal on Emerging Technologies in Computing Systems, 6(3), 11.

    Article  Google Scholar 

  4. Verheijen, H., & Prins, M. (1999). Reversible electrowetting and trapping of charge: Model and experiments. Langmuir, 15, 6616–6620.

    Article  Google Scholar 

  5. Yoon, J.-Y., & Garrell, R. L. (2003). Preventing biomolecular adsorption in electrowetting-based biofluidic chips. Analytical Chemistry, 75, 5097–5102.

    Article  Google Scholar 

  6. Luo, Y., Chakrabarty, K., & Ho, T.-Y. (2013). Error recovery in cyberphysical digital microfluidic biochips. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 32(1), 59–72.

    Article  Google Scholar 

  7. Alistar, M., Pop, P., & Madsen, J. (2015). Redundancy optimization for error recovery in digital microfluidic biochips. Design Automation for Embedded Systems, 19(1–2), 129–159.

    Article  Google Scholar 

  8. Alistar, M., & Pop, P. (2012). Online synthesis for error recovery in digital microfluidic biochips with operation variability. In Proceedings of Symposium on Design, Test, Integration and Packaging of MEMS/MOEMS, pp. 53–58.

    Google Scholar 

  9. Ibrahim, M., & Chakrabarty, K. (2015). Efficient error recovery in cyberphysical digital-microfluidic biochips. IEEE Transactions on Multi-Scale Computing Systems, 1(1), 46–58.

    Article  Google Scholar 

  10. Lai, K. Y.-T., Yang, Y.-T., & Lee, C.-Y. (2015). An intelligent digital microfluidic processor for biomedical detection. Journal of Signal Processing Systems, 78(1), 85–93.

    Article  Google Scholar 

  11. Norman, G., Parker, D., & Sproston, J. (2013). Model checking for probabilistic timed automata. Formal Methods in System Design, 43, 164–190.

    Article  MATH  Google Scholar 

  12. Ho, T.-Y., Chakrabarty, K., & Pop, P. (2011). Digital microfluidic biochips: Recent research and emerging challenges. In Proceedings of ACM/IEEE International Conference on Hardware/Software Codesign and System Synthesis, pp. 335–343.

    Google Scholar 

  13. Chakrabarty, K., & Su, F. (2006). Digital microfluidic biochips: Synthesis, testing, and reconfiguration techniques. Boca Raton: CRC Press.

    Google Scholar 

  14. Su, F., Ozev, S., & Chakrabarty, K. (2003). Testing of droplet-based microelectrofluidic systems. In Proceedings of IEEE International Test Conference, pp. 1192–1200.

    Google Scholar 

  15. Su, F., Chakrabarty, K., & Fair, R. B. (2006). Microfluidics-based biochips: Technology issues, implementation platforms, and design-automation challenges. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 25(2), 211–223.

    Article  Google Scholar 

  16. Xu, T., & Chakrabarty, K. (2007). Functional testing of digital microfluidic biochips. In Proceedings of IEEE International Test Conference, pp. 1–10.

    Google Scholar 

  17. Fair, R. B., Khlystov, A., Tailor, T. D., Ivanov, V., Evans, R. D., Griffin, P. B., et al. (2007). Chemical and biological applications of digital-microfluidic devices. IEEE Design and Test of Computers, 24(1), 10–24.

    Article  Google Scholar 

  18. Zhao, Y., & Chakrabarty, K. (2009). On-line testing of lab-on-chip using reconfigurable digital-microfluidic compactors. International Journal of Parallel Programming, 37(4), 370–388.

    Article  MATH  Google Scholar 

  19. Lai, K. Y.-T., Shiu, M.-F., Lu, Y.-W., Ho, Y.-C., Kao, Y.-C., Yang, Y.-T., et al. (2015). A field-programmable lab-on-a-chip with built-in self-test circuit and low-power sensor-fusion solution in 0.35 μm standard cmos process. In Proceedings of IEEE Asian Solid-State Circuits Conference, pp. 1–4.

    Google Scholar 

  20. Fair, R., Srinivasan, V., Ren, H., Paik, P., Pamula, V., & Pollack, M. (2003). Electrowetting-based on-chip sample processing for integrated microfluidics. In Proceedings of IEEE International Electron Devices Meeting, pp. 32–35.

    Google Scholar 

  21. Brémaud, P. (2013) Markov Chains: Gibbs Fields, Monte Carlo Simulation, and Queues. New York: Springer Science and Business Media.

    MATH  Google Scholar 

  22. Su, F., & Chakrabarty, K. (2008). High-level synthesis of digital microfluidic biochips. ACM Journal on Emerging Technologies in Computing Systems, 3(4), 1.

    Article  Google Scholar 

  23. Kwiatkowska, M., Norman, G., & Parker, D. (2011). Prism 4.0: Verification of probabilistic real-time systems. In Proceedings of International Conference Computer Aided Verification, pp. 585–591.

    Chapter  Google Scholar 

  24. Bertsimas, D., & Tsitsiklis, J. (1997). Introduction to linear optimization. Belmont: Athena Scientific.

    Google Scholar 

  25. Luo, Y., Chakrabarty, K., & Ho, T.-Y. (2012). A cyberphysical synthesis approach for error recovery in digital microfluidic biochips. In Proceedings of IEEE/ACM Design, Automation and Test Conference in Europe, pp. 1239–1244.

    Google Scholar 

  26. Li, Z., Lai, K. Y.-T., Yu, P.-H., Ho, T.-Y., Chakrabarty, K., & Lee, C.-Y. (2016). High-level synthesis for micro-electrode-dot-array digital microfluidic biochips. In Proceedings of ACM/IEEE Design Automation Conference (pp. 146:1–146:6). New York: ACM.

    Google Scholar 

  27. Su, F., & Chakrabarty, K. (2005). Unified high-level synthesis and module placement for defect-tolerant microfluidic biochips. In Proceedings of ACM/IEEE Design Automation Conference, pp. 825–830.

    Google Scholar 

  28. Su, F., Hwang, W., & Chakrabarty, K. (2006). Droplet routing in the synthesis of digital microfluidic biochips. In Proceedings of IEEE/ACM Design, Automation and Test Conference in Europe, 1, pp. 1–6.

    Google Scholar 

  29. Zhao, Y., & Chakrabarty, K. (2012). Cross-contamination avoidance for droplet routing in digital microfluidic biochips. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 31(6), 817–830.

    Article  Google Scholar 

  30. Huang, T.-W., & Ho, T.-Y. (2011). A two-stage integer linear programming-based droplet routing algorithm for pin-constrained digital microfluidic biochips. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 30, 215–228.

    Article  Google Scholar 

  31. Roy, P., Rahaman, H., & Dasgupta, P. (2010). A novel droplet routing algorithm for digital microfluidic biochips. In Proceedings of ACM Great Lakes Symposium on VLSI (pp. 441–446). New York: ACM.

    Google Scholar 

  32. Chen, Z., Teng, D. H.-Y., Wang, G. C.-J., & Fan, S.-K. (2011). Droplet routing in high-level synthesis of configurable digital microfluidic biochips based on microelectrode dot array architecture. Biochip Journal, 5(4), 343–352.

    Article  Google Scholar 

  33. Wang, G., Teng, D., & Fan, S.-K. (2011). Digital microfluidic operations on micro-electrode dot array architecture. IET Nanobiotechnology, 5(4), 152–160.

    Article  Google Scholar 

  34. Li, Z., Lai, K. Y.-T., Yu, P.-H., Chakrabarty, K., Ho, T.-Y., & Lee, C.-Y. (2017). Droplet size-aware high-level synthesis for micro-electrode-dot-array digital microfluidic biochips. IEEE Transactions on Biomedical Circuits and Systems, 11(3), 612–626.

    Article  Google Scholar 

  35. Trivedi, K. S. (2008). Probability and statistics with reliability, queueing, and computer science applications. New York: John Wiley and Sons.

    Google Scholar 

  36. Gefen, A. (2009). Bioengineering research of chronic wounds: A multidisciplinary study approach. New York: Springer Science and Business Media.

    Book  Google Scholar 

  37. Fei, S. (2004). Module placement for fault-tolerant microfluidics-based biochips. ACM Transactions on Design Automation of Electronic Systems, 11(3), 682–710.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Intel (United States), Santa Clara, CA, USA

    Zipeng Li

  2. Department of ECE, Duke University, Durham, NC, USA

    Krishnendu Chakrabarty

  3. National Tsing Hua University, Hsinchu, Taiwan

    Tsung-Yi Ho

  4. National Chiao Tung University, Hsinchu, Taiwan

    Chen-Yi Lee

Authors
  1. Zipeng Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Krishnendu Chakrabarty
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Tsung-Yi Ho
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Chen-Yi Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Li, Z., Chakrabarty, K., Ho, TY., Lee, CY. (2019). Efficient and Adaptive Error Recovery. In: Micro-Electrode-Dot-Array Digital Microfluidic Biochips. Springer, Cham. https://doi.org/10.1007/978-3-030-02964-7_3

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-02964-7_3

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-02963-0

  • Online ISBN: 978-3-030-02964-7

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation