Multichannel evoked neural signal compression using advanced video compression algorithm

Han Chung Chen; Liang Gee Chen; Yu Chieh Kao; Fu Shan Jaw

doi:10.1109/NER.2009.5109392

Multichannel evoked neural signal compression using advanced video compression algorithm

Han Chung Chen, Liang Gee Chen, Yu Chieh Kao, Fu Shan Jaw

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

8 Citations (Scopus)

Abstract

Multichannel neural recording is one of the most important topics in the field of biomedical engineering. This is because there is a need to considerably reduce large amounts of data without degrading the data quality for easy transfer through wireless transmission. Video compression technology is of considerable importance in the field of signal processing. There are many similarities between multichannel neural signals and video signals. In this study, we propose a signal compression method that employs motion vectors (MVs) to reduce the redundancy between successive video frames and between successive channels. The method shows a signal-to-noise (error) ratio (SNR) of 25 db and data are compressed to 5% of their original size.

Original language	English
Title of host publication	2009 4th International IEEE/EMBS Conference on Neural Engineering, NER '09
Pages	697-701
Number of pages	5
DOIs	https://doi.org/10.1109/NER.2009.5109392
Publication status	Published - Oct 27 2009
Externally published	Yes
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/Territory	Turkey
City	Antalya
Period	4/29/09 → 5/2/09

Keywords

Biomedical signal processing
Multielectrode signals
Video signal processing

ASJC Scopus subject areas

Biomedical Engineering
Clinical Neurology
General Neuroscience

Access to Document

10.1109/NER.2009.5109392

Cite this

Chen, H. C., Chen, L. G., Kao, Y. C., & Jaw, F. S. (2009). Multichannel evoked neural signal compression using advanced video compression algorithm. In 2009 4th International IEEE/EMBS Conference on Neural Engineering, NER '09 (pp. 697-701). Article 5109392 (2009 4th International IEEE/EMBS Conference on Neural Engineering, NER '09). https://doi.org/10.1109/NER.2009.5109392

Multichannel evoked neural signal compression using advanced video compression algorithm. / Chen, Han Chung; Chen, Liang Gee; Kao, Yu Chieh et al.
2009 4th International IEEE/EMBS Conference on Neural Engineering, NER '09. 2009. p. 697-701 5109392 (2009 4th International IEEE/EMBS Conference on Neural Engineering, NER '09).

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

Chen, HC, Chen, LG, Kao, YC & Jaw, FS 2009, Multichannel evoked neural signal compression using advanced video compression algorithm. in 2009 4th International IEEE/EMBS Conference on Neural Engineering, NER '09., 5109392, 2009 4th International IEEE/EMBS Conference on Neural Engineering, NER '09, pp. 697-701, 2009 4th International IEEE/EMBS Conference on Neural Engineering, NER '09, Antalya, Turkey, 4/29/09. https://doi.org/10.1109/NER.2009.5109392

@inproceedings{086f57d023d7414d9414ca2c4cc4bdac,

title = "Multichannel evoked neural signal compression using advanced video compression algorithm",

abstract = "Multichannel neural recording is one of the most important topics in the field of biomedical engineering. This is because there is a need to considerably reduce large amounts of data without degrading the data quality for easy transfer through wireless transmission. Video compression technology is of considerable importance in the field of signal processing. There are many similarities between multichannel neural signals and video signals. In this study, we propose a signal compression method that employs motion vectors (MVs) to reduce the redundancy between successive video frames and between successive channels. The method shows a signal-to-noise (error) ratio (SNR) of 25 db and data are compressed to 5% of their original size.",

keywords = "Biomedical signal processing, Multielectrode signals, Video signal processing",

author = "Chen, {Han Chung} and Chen, {Liang Gee} and Kao, {Yu Chieh} and Jaw, {Fu Shan}",

year = "2009",

month = oct,

day = "27",

doi = "10.1109/NER.2009.5109392",

language = "English",

isbn = "9781424420735",

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

pages = "697--701",

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 - Multichannel evoked neural signal compression using advanced video compression algorithm

AU - Chen, Han Chung

AU - Chen, Liang Gee

AU - Kao, Yu Chieh

AU - Jaw, Fu Shan

PY - 2009/10/27

Y1 - 2009/10/27

N2 - Multichannel neural recording is one of the most important topics in the field of biomedical engineering. This is because there is a need to considerably reduce large amounts of data without degrading the data quality for easy transfer through wireless transmission. Video compression technology is of considerable importance in the field of signal processing. There are many similarities between multichannel neural signals and video signals. In this study, we propose a signal compression method that employs motion vectors (MVs) to reduce the redundancy between successive video frames and between successive channels. The method shows a signal-to-noise (error) ratio (SNR) of 25 db and data are compressed to 5% of their original size.

AB - Multichannel neural recording is one of the most important topics in the field of biomedical engineering. This is because there is a need to considerably reduce large amounts of data without degrading the data quality for easy transfer through wireless transmission. Video compression technology is of considerable importance in the field of signal processing. There are many similarities between multichannel neural signals and video signals. In this study, we propose a signal compression method that employs motion vectors (MVs) to reduce the redundancy between successive video frames and between successive channels. The method shows a signal-to-noise (error) ratio (SNR) of 25 db and data are compressed to 5% of their original size.

KW - Biomedical signal processing

KW - Multielectrode signals

KW - Video signal processing

UR - http://www.scopus.com/inward/record.url?scp=70350218886&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=70350218886&partnerID=8YFLogxK

U2 - 10.1109/NER.2009.5109392

DO - 10.1109/NER.2009.5109392

M3 - Conference contribution

AN - SCOPUS:70350218886

SN - 9781424420735

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

SP - 697

EP - 701

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 -

Multichannel evoked neural signal compression using advanced video compression algorithm

Abstract

Publication series

Other

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this