Compression of neural signals using discriminative coding for wireless applications

Stefan Craciun; David Cheney; Karl Gugel; Justin C. Sanchez; Jose C. Principe

doi:10.1109/NER.2009.5109375

Compression of neural signals using discriminative coding for wireless applications

Stefan Craciun, David Cheney, Karl Gugel, Justin C. Sanchez, Jose C. Principe

Biomedical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

9 Scopus citations

Abstract

One of the most critical tasks when designing a portable wireless neural recording system is to limit power consumption. This paper proposes a new compression technique applied to neuronal recordings in real-time. The signal is compressed before transmission using a discriminative vector quantization algorithm and then it is reconstructed on the receiver side. Results show that power consumption is decreased while more efficiently using the limited bandwidth. A discriminative Linde-Buzo-Gray algorithm (DLBG) preserves action potential regions of the neuronal signal where information is contained while efficiently filtering background activity. The compression algorithm has been tested in real time on a hardware platform (PICO DSP [3]) that has a Digital Signal Processor (DSP) which performs the algorithm before sending the compressed data to a wireless transmitter. The compression ratios obtained range between 20:1 and 70:1 depending on the embedding size of the signal and the number of code-vectors used.

Original language	English (US)
Title of host publication	2009 4th International IEEE/EMBS Conference on Neural Engineering, NER '09
Pages	629-632
Number of pages	4
DOIs	https://doi.org/10.1109/NER.2009.5109375
State	Published - Oct 27 2009
Event	2009 4th International IEEE/EMBS Conference on Neural Engineering, NER '09 - Antalya, Turkey Duration: Apr 29 2009 → May 2 2009

Publication series

Name	2009 4th International IEEE/EMBS Conference on Neural Engineering, NER '09

Other

Other	2009 4th International IEEE/EMBS Conference on Neural Engineering, NER '09
Country	Turkey
City	Antalya
Period	4/29/09 → 5/2/09

ASJC Scopus subject areas

Biomedical Engineering
Clinical Neurology
Neuroscience(all)

Access to Document

10.1109/NER.2009.5109375

Fingerprint Dive into the research topics of 'Compression of neural signals using discriminative coding for wireless applications'. Together they form a unique fingerprint.

Cite this

Craciun, S., Cheney, D., Gugel, K., Sanchez, J. C., & Principe, J. C. (2009). Compression of neural signals using discriminative coding for wireless applications. In 2009 4th International IEEE/EMBS Conference on Neural Engineering, NER '09 (pp. 629-632). [5109375] (2009 4th International IEEE/EMBS Conference on Neural Engineering, NER '09). https://doi.org/10.1109/NER.2009.5109375

Compression of neural signals using discriminative coding for wireless applications. / Craciun, Stefan; Cheney, David; Gugel, Karl; Sanchez, Justin C.; Principe, Jose C.

2009 4th International IEEE/EMBS Conference on Neural Engineering, NER '09. 2009. p. 629-632 5109375 (2009 4th International IEEE/EMBS Conference on Neural Engineering, NER '09).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Craciun, S, Cheney, D, Gugel, K, Sanchez, JC & Principe, JC 2009, Compression of neural signals using discriminative coding for wireless applications. in 2009 4th International IEEE/EMBS Conference on Neural Engineering, NER '09., 5109375, 2009 4th International IEEE/EMBS Conference on Neural Engineering, NER '09, pp. 629-632, 2009 4th International IEEE/EMBS Conference on Neural Engineering, NER '09, Antalya, Turkey, 4/29/09. https://doi.org/10.1109/NER.2009.5109375

@inproceedings{dc9fe5cfff964bd38762902b6285a5dc,

title = "Compression of neural signals using discriminative coding for wireless applications",

abstract = "One of the most critical tasks when designing a portable wireless neural recording system is to limit power consumption. This paper proposes a new compression technique applied to neuronal recordings in real-time. The signal is compressed before transmission using a discriminative vector quantization algorithm and then it is reconstructed on the receiver side. Results show that power consumption is decreased while more efficiently using the limited bandwidth. A discriminative Linde-Buzo-Gray algorithm (DLBG) preserves action potential regions of the neuronal signal where information is contained while efficiently filtering background activity. The compression algorithm has been tested in real time on a hardware platform (PICO DSP [3]) that has a Digital Signal Processor (DSP) which performs the algorithm before sending the compressed data to a wireless transmitter. The compression ratios obtained range between 20:1 and 70:1 depending on the embedding size of the signal and the number of code-vectors used.",

author = "Stefan Craciun and David Cheney and Karl Gugel and Sanchez, {Justin C.} and Principe, {Jose C.}",

year = "2009",

month = oct,

day = "27",

doi = "10.1109/NER.2009.5109375",

language = "English (US)",

isbn = "9781424420735",

series = "2009 4th International IEEE/EMBS Conference on Neural Engineering, NER '09",

pages = "629--632",

booktitle = "2009 4th International IEEE/EMBS Conference on Neural Engineering, NER '09",

note = "2009 4th International IEEE/EMBS Conference on Neural Engineering, NER '09 ; Conference date: 29-04-2009 Through 02-05-2009",

}

TY - GEN

T1 - Compression of neural signals using discriminative coding for wireless applications

AU - Craciun, Stefan

AU - Cheney, David

AU - Gugel, Karl

AU - Sanchez, Justin C.

AU - Principe, Jose C.

PY - 2009/10/27

Y1 - 2009/10/27

N2 - One of the most critical tasks when designing a portable wireless neural recording system is to limit power consumption. This paper proposes a new compression technique applied to neuronal recordings in real-time. The signal is compressed before transmission using a discriminative vector quantization algorithm and then it is reconstructed on the receiver side. Results show that power consumption is decreased while more efficiently using the limited bandwidth. A discriminative Linde-Buzo-Gray algorithm (DLBG) preserves action potential regions of the neuronal signal where information is contained while efficiently filtering background activity. The compression algorithm has been tested in real time on a hardware platform (PICO DSP [3]) that has a Digital Signal Processor (DSP) which performs the algorithm before sending the compressed data to a wireless transmitter. The compression ratios obtained range between 20:1 and 70:1 depending on the embedding size of the signal and the number of code-vectors used.

AB - One of the most critical tasks when designing a portable wireless neural recording system is to limit power consumption. This paper proposes a new compression technique applied to neuronal recordings in real-time. The signal is compressed before transmission using a discriminative vector quantization algorithm and then it is reconstructed on the receiver side. Results show that power consumption is decreased while more efficiently using the limited bandwidth. A discriminative Linde-Buzo-Gray algorithm (DLBG) preserves action potential regions of the neuronal signal where information is contained while efficiently filtering background activity. The compression algorithm has been tested in real time on a hardware platform (PICO DSP [3]) that has a Digital Signal Processor (DSP) which performs the algorithm before sending the compressed data to a wireless transmitter. The compression ratios obtained range between 20:1 and 70:1 depending on the embedding size of the signal and the number of code-vectors used.

UR - http://www.scopus.com/inward/record.url?scp=70350227369&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=70350227369&partnerID=8YFLogxK

U2 - 10.1109/NER.2009.5109375

DO - 10.1109/NER.2009.5109375

M3 - Conference contribution

AN - SCOPUS:70350227369

SN - 9781424420735

T3 - 2009 4th International IEEE/EMBS Conference on Neural Engineering, NER '09

SP - 629

EP - 632

BT - 2009 4th International IEEE/EMBS Conference on Neural Engineering, NER '09

T2 - 2009 4th International IEEE/EMBS Conference on Neural Engineering, NER '09

Y2 - 29 April 2009 through 2 May 2009

ER -