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 proceedingConference contribution

7 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 languageEnglish
Title of host publication2009 4th International IEEE/EMBS Conference on Neural Engineering, NER '09
Pages697-701
Number of pages5
DOIs
Publication statusPublished - Oct 27 2009
Externally publishedYes
Event2009 4th International IEEE/EMBS Conference on Neural Engineering, NER '09 - Antalya, Turkey
Duration: Apr 29 2009May 2 2009

Publication series

Name2009 4th International IEEE/EMBS Conference on Neural Engineering, NER '09

Other

Other2009 4th International IEEE/EMBS Conference on Neural Engineering, NER '09
CountryTurkey
CityAntalya
Period4/29/095/2/09

Keywords

  • Biomedical signal processing
  • Multielectrode signals
  • Video signal processing

ASJC Scopus subject areas

  • Biomedical Engineering
  • Clinical Neurology
  • Neuroscience(all)

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  • 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). [5109392] (2009 4th International IEEE/EMBS Conference on Neural Engineering, NER '09). https://doi.org/10.1109/NER.2009.5109392