Analyzing power spectral of electroencephalogram (EEG) signal to identify motoric arm movement using EMOTIV EPOC+

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Rehabilitation of motoric dysfunction from the body becomes the main objective of developing Brain Computer Interface (BCI) technique, especially in the field of medical rehabilitation technology. BCI technology based on electrical activity of the brain, allow patient to be able to restore motoric disfunction of the body and help them to overcome the shortcomings mobility. In this study, EEG signal phenomenon was obtained from EMOTIV EPOC+, the signals were generated from the imagery of lifting arm, and look for any correlation between the imagery of motoric muscle movement against the recorded signals. The signals processing were done in the time-frequency domain, using Wavelet relative power (WRP) as feature extraction, and Support vector machine (SVM) as the classifier. In this study, it was obtained the result of maximum accuracy of 81.3 % using 8 channel (AF3, F7, F3, FC5, FC6, F4, F8, and AF4), 6 channel remaining on EMOTIV EPOC + does not contribute to the improvement of the accuracy of the classification system.

Original languageEnglish
Title of host publicationInternational Symposium on Current Progress in Mathematics and Sciences 2016, ISCPMS 2016
Subtitle of host publicationProceedings of the 2nd International Symposium on Current Progress in Mathematics and Sciences 2016
EditorsKiki Ariyanti Sugeng, Djoko Triyono, Terry Mart
PublisherAmerican Institute of Physics Inc.
ISBN (Electronic)9780735415362
DOIs
Publication statusPublished - 10 Jul 2017
Event2nd International Symposium on Current Progress in Mathematics and Sciences 2016, ISCPMS 2016 - Depok, Jawa Barat, Indonesia
Duration: 1 Nov 20162 Nov 2016

Publication series

NameAIP Conference Proceedings
Volume1862
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Conference

Conference2nd International Symposium on Current Progress in Mathematics and Sciences 2016, ISCPMS 2016
CountryIndonesia
CityDepok, Jawa Barat
Period1/11/162/11/16

Fingerprint Dive into the research topics of 'Analyzing power spectral of electroencephalogram (EEG) signal to identify motoric arm movement using EMOTIV EPOC+'. Together they form a unique fingerprint.

Cite this