TY - JOUR
T1 - Use of dry electroencephalogram and support vector for objective pain assessment
AU - Okolo, Chika
AU - Omurtag, Ahmet
N1 - Publisher Copyright:
© 2018 AAMI.
PY - 2018/9/1
Y1 - 2018/9/1
N2 - The reliability of normal gel-based electrode electroencephalogram (EEG) for measuring pain has been validated. To date, however, few documented trials have used dry EEG for pain quantification. The primary goal of this study was to objectively quantify pain using dry EEG in conjunction with a support vector machine (SVM). SVMs have been proven accurate for classifying pain intensity. The authors believe that EEG combined with an SVM could increase the statistical power of pain assessment. Currently, clinicians primarily rely on verbal (i.e., subjective) reports for assessing pain; therefore, the research described here could offer a method to objectively monitor pain, eliminate observer error, and individualize treatment.
AB - The reliability of normal gel-based electrode electroencephalogram (EEG) for measuring pain has been validated. To date, however, few documented trials have used dry EEG for pain quantification. The primary goal of this study was to objectively quantify pain using dry EEG in conjunction with a support vector machine (SVM). SVMs have been proven accurate for classifying pain intensity. The authors believe that EEG combined with an SVM could increase the statistical power of pain assessment. Currently, clinicians primarily rely on verbal (i.e., subjective) reports for assessing pain; therefore, the research described here could offer a method to objectively monitor pain, eliminate observer error, and individualize treatment.
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U2 - 10.2345/0899-8205-52.5.372
DO - 10.2345/0899-8205-52.5.372
M3 - Article
C2 - 30260658
AN - SCOPUS:85054575145
SN - 0899-8205
VL - 52
SP - 372
EP - 378
JO - Biomedical Instrumentation and Technology
JF - Biomedical Instrumentation and Technology
IS - 5
ER -