Energy-efficient reconstruction of compressively sensed bioelectrical signals with stochastic computing circuits

Yufei Ma, Minkyu Kim, Yu Cao, Jae-sun Seo, Sarma Vrudhula

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Compressive sensing (CS) allows acquiring sparse signals at sub-Nyquist rate, offering an energy-efficient solution to data acquisition. This is especially important to reduce communication data for mobile medical applications. However, reconstructing the signal from CS is usually left off-line due to the complex computations. In this paper, we integrate two key technologies to enable on-line energy-efficient CS signal reconstruction. These are (1) the use of Bayesian CS Belief Propagation (CS-BP) as the algorithm basis and (2) the novel design of stochastic computing (SC) circuits to efficiently map CS-BP algorithm. The overall signal reconstruction system is implemented with digital SC circuits in 65nm CMOS and recovers compressively sensed electrocardiography (ECG) and electromyography (EMG) signals with 11X to 8X data compression factor. Compared to a conventional binary design, post-layout simulation results show that the proposed stochastic design performs reconstruction with 5X energy-delay product improvement and 2X area reduction.

Original languageEnglish (US)
Title of host publicationProceedings of the 33rd IEEE International Conference on Computer Design, ICCD 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages443-446
Number of pages4
ISBN (Print)9781467371650
DOIs
StatePublished - Dec 14 2015
Event33rd IEEE International Conference on Computer Design, ICCD 2015 - New York City, United States
Duration: Oct 18 2015Oct 21 2015

Other

Other33rd IEEE International Conference on Computer Design, ICCD 2015
CountryUnited States
CityNew York City
Period10/18/1510/21/15

Fingerprint

Signal reconstruction
Networks (circuits)
Electromyography
Data compression
Medical applications
Electrocardiography
Data acquisition
Communication

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Computer Science Applications

Cite this

Ma, Y., Kim, M., Cao, Y., Seo, J., & Vrudhula, S. (2015). Energy-efficient reconstruction of compressively sensed bioelectrical signals with stochastic computing circuits. In Proceedings of the 33rd IEEE International Conference on Computer Design, ICCD 2015 (pp. 443-446). [7357144] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCD.2015.7357144

Energy-efficient reconstruction of compressively sensed bioelectrical signals with stochastic computing circuits. / Ma, Yufei; Kim, Minkyu; Cao, Yu; Seo, Jae-sun; Vrudhula, Sarma.

Proceedings of the 33rd IEEE International Conference on Computer Design, ICCD 2015. Institute of Electrical and Electronics Engineers Inc., 2015. p. 443-446 7357144.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Ma, Y, Kim, M, Cao, Y, Seo, J & Vrudhula, S 2015, Energy-efficient reconstruction of compressively sensed bioelectrical signals with stochastic computing circuits. in Proceedings of the 33rd IEEE International Conference on Computer Design, ICCD 2015., 7357144, Institute of Electrical and Electronics Engineers Inc., pp. 443-446, 33rd IEEE International Conference on Computer Design, ICCD 2015, New York City, United States, 10/18/15. https://doi.org/10.1109/ICCD.2015.7357144
Ma Y, Kim M, Cao Y, Seo J, Vrudhula S. Energy-efficient reconstruction of compressively sensed bioelectrical signals with stochastic computing circuits. In Proceedings of the 33rd IEEE International Conference on Computer Design, ICCD 2015. Institute of Electrical and Electronics Engineers Inc. 2015. p. 443-446. 7357144 https://doi.org/10.1109/ICCD.2015.7357144
Ma, Yufei ; Kim, Minkyu ; Cao, Yu ; Seo, Jae-sun ; Vrudhula, Sarma. / Energy-efficient reconstruction of compressively sensed bioelectrical signals with stochastic computing circuits. Proceedings of the 33rd IEEE International Conference on Computer Design, ICCD 2015. Institute of Electrical and Electronics Engineers Inc., 2015. pp. 443-446
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