Use of dry-electroencephalogram and support vector for objective pain assessment

Okolo, C. and Omurtag, A. ORCID: 0000-0002-3773-8506, 2018. Use of dry-electroencephalogram and support vector for objective pain assessment. Biomedical Instrumentation & Technology, 52 (5), pp. 372-378. ISSN 0899-8205

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Abstract

Our primary goal was to objectively quantify pain. The experiment we designated for this task was via dry electroencephalography (EEG) in conjunction with a support vector machine classifier (SVM). Normal gel-based electrode EEG has been validated as reliable in pain measurement. Yet, to date, there are few documented trials that use dry-EEG for pain quantification. In addition, SVM classifiers have proven accurate when classifying pain intensity. Therefore, we believe EEG combined with SVM could increase the statistical power of pain assessment. However, due to the subjectivity of pain, currently clinicians mainly rely on verbal reports. This research could offer a method to objectively monitor pain, eliminate observer error and individualize treatment.

Item Type: Journal article
Publication Title: Biomedical Instrumentation & Technology
Creators: Okolo, C. and Omurtag, A.
Publisher: Association for the Advancement of Medical Instrumentation
Date: September 2018
Volume: 52
Number: 5
ISSN: 0899-8205
Identifiers:
NumberType
10.2345/0899-8205-52.5.372DOI
Divisions: Schools > School of Science and Technology
Depositing User: Jonathan Gallacher
Date Added: 02 May 2018 08:13
Last Modified: 17 Sep 2019 15:42
URI: http://irep.ntu.ac.uk/id/eprint/33417

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