A somatosensory evoked potential monitoring algorithm using time frequency filtering

S. M.Amin Motahari, Krishnatej Vedala, Mohammed Goryawala, Mercedes Cabrerizo, Ilker Yaylali, Malek Adjouadi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

A new method of detecting somatosensory evoked potentials (SSEP) is proposed using a time-frequency based windowing to enhance the signal to noise ratio (SNR) of the recorded SSEP signals. A sequential computation of maxima and minima was then used to find the location of characteristic positive and negative peaks of the SSEP. The algorithm rejects trials with high peak value as they are corrupted with noise. The performance of the proposed algorithm was observed to be within acceptable clinical margins even with the use of only 30 consecutive trials at a time, thus proving to be very efficient for intraoperative neurophysiological monitoring during surgical procedures.

Original languageEnglish (US)
Title of host publication2013 6th International IEEE EMBS Conference on Neural Engineering, NER 2013
Pages351-354
Number of pages4
DOIs
StatePublished - 2013
Externally publishedYes
Event2013 6th International IEEE EMBS Conference on Neural Engineering, NER 2013 - San Diego, CA, United States
Duration: Nov 6 2013Nov 8 2013

Publication series

NameInternational IEEE/EMBS Conference on Neural Engineering, NER
ISSN (Print)1948-3546
ISSN (Electronic)1948-3554

Other

Other2013 6th International IEEE EMBS Conference on Neural Engineering, NER 2013
Country/TerritoryUnited States
CitySan Diego, CA
Period11/6/1311/8/13

ASJC Scopus subject areas

  • Artificial Intelligence
  • Mechanical Engineering

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