Separation of multi-channel spinal cord recordings using unsupervised adaptive filtering

Yanmei Tie, Mesut Sahin

Research output: Contribution to journalConference articlepeer-review

3 Scopus citations


In anesthetized animals, evoked motor signals descending through the corticospinal tract were recorded from the spinal cord with selectivity using multi-contact surface electrodes [1]. However, the spatial selectivity needs to be improved for this approach to be used as a multi-channel neural interface. In this study, we applied the blind source separation (BBS) technique to improve the separation between the neural channels. The BSS algorithm improved the selectivity from an initial value of less than 1% to 91% although the signal-to-noise ratio of the signals was as low as 0.46 on average.

Original languageEnglish (US)
Pages (from-to)2014-2015
Number of pages2
JournalAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
StatePublished - 2002
Externally publishedYes
EventProceedings of the 2002 IEEE Engineering in Medicine and Biology 24th Annual Conference and the 2002 Fall Meeting of the Biomedical Engineering Society (BMES / EMBS) - Houston, TX, United States
Duration: Oct 23 2002Oct 26 2002

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Health Informatics
  • Computer Vision and Pattern Recognition
  • Biomedical Engineering


  • Blind source separation
  • Independent component analysis
  • Selective neural recording
  • Signal to noise ratio


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