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Low-power hardware implementation of movement decoding for brain computer interface with reduced-resolution discrete cosine transform.

Publication ,  Conference
Minho Won, ; Albalawi, H; Xin Li, ; Thomas, DE
Published in: Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
January 2014

This paper describes a low-power hardware implementation for movement decoding of brain computer interface. Our proposed hardware design is facilitated by two novel ideas: (i) an efficient feature extraction method based on reduced-resolution discrete cosine transform (DCT), and (ii) a new hardware architecture of dual look-up table to perform discrete cosine transform without explicit multiplication. The proposed hardware implementation has been validated for movement decoding of electrocorticography (ECoG) signal by using a Xilinx FPGA Zynq-7000 board. It achieves more than 56× energy reduction over a reference design using band-pass filters for feature extraction.

Duke Scholars

Published In

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference

DOI

EISSN

2694-0604

ISSN

2375-7477

Publication Date

January 2014

Volume

2014

Start / End Page

1626 / 1629

Related Subject Headings

  • Movement
  • Humans
  • Equipment Design
  • Electrocorticography
  • Electric Power Supplies
  • Computers
  • Brain-Computer Interfaces
  • Algorithms
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Minho Won, ., Albalawi, H., Xin Li, ., & Thomas, D. E. (2014). Low-power hardware implementation of movement decoding for brain computer interface with reduced-resolution discrete cosine transform. In Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference (Vol. 2014, pp. 1626–1629). https://doi.org/10.1109/embc.2014.6943916
Minho Won, B. F., Hassan Albalawi, Hassan Xin Li, and Donald E. Thomas. “Low-power hardware implementation of movement decoding for brain computer interface with reduced-resolution discrete cosine transform.” In Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, 2014:1626–29, 2014. https://doi.org/10.1109/embc.2014.6943916.
Minho Won, Albalawi H, Xin Li, Thomas DE. Low-power hardware implementation of movement decoding for brain computer interface with reduced-resolution discrete cosine transform. In: Annual International Conference of the IEEE Engineering in Medicine and Biology Society IEEE Engineering in Medicine and Biology Society Annual International Conference. 2014. p. 1626–9.
Minho Won, B. F., et al. “Low-power hardware implementation of movement decoding for brain computer interface with reduced-resolution discrete cosine transform.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, vol. 2014, 2014, pp. 1626–29. Epmc, doi:10.1109/embc.2014.6943916.
Minho Won, Albalawi H, Xin Li, Thomas DE. Low-power hardware implementation of movement decoding for brain computer interface with reduced-resolution discrete cosine transform. Annual International Conference of the IEEE Engineering in Medicine and Biology Society IEEE Engineering in Medicine and Biology Society Annual International Conference. 2014. p. 1626–1629.

Published In

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference

DOI

EISSN

2694-0604

ISSN

2375-7477

Publication Date

January 2014

Volume

2014

Start / End Page

1626 / 1629

Related Subject Headings

  • Movement
  • Humans
  • Equipment Design
  • Electrocorticography
  • Electric Power Supplies
  • Computers
  • Brain-Computer Interfaces
  • Algorithms