DocumentCode :
662957
Title :
A somatosensory evoked potential monitoring algorithm using time frequency filtering
Author :
Motahari, S. M. Amin ; Vedala, Krishnatej ; Goryawala, Mohammed ; Cabrerizo, Mercedes ; Yaylali, Ilker ; Adjouadi, Malek
Author_Institution :
Center for Adv. Technol. & Educ, FIU Coll. of Eng. & Comput., Miami, FL, USA
fYear :
2013
fDate :
6-8 Nov. 2013
Firstpage :
351
Lastpage :
354
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.
Keywords :
bioelectric potentials; filtering theory; medical signal detection; neurophysiology; patient monitoring; somatosensory phenomena; surgery; SNR; intraoperative neurophysiological monitoring; recorded SSEP signals; signal-to-noise ratio; somatosensory evoked potential detection; somatosensory evoked potential monitoring algorithm; surgical procedures; time frequency filtering; time-frequency based windowing; Band-pass filters; Detectors; Electric potential; Monitoring; Neurophysiology; Surgery; Time-domain analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Engineering (NER), 2013 6th International IEEE/EMBS Conference on
Conference_Location :
San Diego, CA
ISSN :
1948-3546
Type :
conf
DOI :
10.1109/NER.2013.6695944
Filename :
6695944
Link To Document :
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