DocumentCode :
1555306
Title :
Quality estimation of subdurally recorded, event-related potentials based on signal-to-noise ratio
Author :
Rohde, Mitchell M. ; BeMent, Spencer L. ; Huggins, Jane E. ; Levine, Simon P. ; Kushwaha, Ramesh K. ; Schuh, Lori A.
Author_Institution :
Michigan Univ., Ann Arbor, MI, USA
Volume :
49
Issue :
1
fYear :
2002
fDate :
1/1/2002 12:00:00 AM
Firstpage :
31
Lastpage :
40
Abstract :
Our goal is to develop a direct brain interface (DBI) that will provide communication and environmental control to persons who are "locked-in" (or nearly so) as a consequence of brainstem stroke, amyotrophic lateral sclerosis (ALS), or other etiologies. Previously we demonstrated that templates constructed from trigger averaged event-related potentials (ERPs) can be cross-correlated with ongoing electrocorticograms (ECoGs) to detect ERPs associated with the performance of simple motor actions. However, it was difficult to predict a priori which of many candidate ECoG recording site(s) could provide signals that would provide adequate motor action detection. We present here a measure of ERP quality based on an estimate of the signal to noise ratio (SNR) associated with the formation of an ERP template from the performance of consecutive voluntary actions. Detection-theory-based receiver operator characteristics (ROCs) and a database of ECoGs (6000+) recorded from the cortical surface of awake human subjects were used to assess the usefulness of the SNR technique. The SNR method was found to predict the detection efficacy of ERPs when characterized over a wide parameter range, with the majority of ROC curve areas greater than 90%. This method was compared with our previously developed quality measure (the peak-to-baseline ratio) and found to provide significantly better performance (ROC area differences from 4.4% to 13.7%). Thus, the SNR estimate of the ERP is a useful tool to predict the efficacy of ERP templates for cross-correlation-based detection and assist in the selection of viable ERP templates for DBI applications
Keywords :
biocontrol; electroencephalography; handicapped aids; medical signal processing; quality control; ECoGs database; ERP template; assistive technology; brain-computer interface; communication control; detection-theory-based receiver operator characteristics; direct brain interface; electrocorticogram; environmental control; event-related potential; locked-in syndrome patients; quality estimation; signal-to-noise ratio; subdurally recorded event-related potentials; Biomedical engineering; Biomedical measurements; Brain computer interfaces; Communication system control; Databases; Enterprise resource planning; Humans; Nervous system; Noise measurement; Signal to noise ratio;
fLanguage :
English
Journal_Title :
Biomedical Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9294
Type :
jour
DOI :
10.1109/10.972837
Filename :
972837
Link To Document :
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