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Brain Computer Interface-Based Algorithm For The Detection Of Finger Movement
KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
University of Belgrade, Sebia.
2012 (English)Conference paper, Poster (Refereed)
Abstract [en]

User of Brain Computer Interface system stays in “idle state” between executions of motor task or imagining one. Movement-based BCIs can operate in synchronous and asynchronous mode and in both cases in order to make the system robust, it is necessary that the system is able to distinguish with certainty idle state from the initiation of the movement. We propose computing method that determines the probability of subject's intention to make movement in comparison to idle state. We therefore asked 4 subjects between 20-30 years of age to perform the task of pressing the taster button by thumb while their EEG recordings were obtained. First, the subjects performed motor task at instants defined with the animation shown on screen and second, subjects performed self-initiated movement. Movement onsets were identified by voltage change when taster sensor was pressed while analysis was based on the Event Related Desynchronisation (ERD). This neurophysiological phenomenon refers to the decrease of the EEG signal power just before the voluntary movement onset (pre-movement state). Features of the extracted signals were determined by applying one of the following methods: Welch's method, Burg's algorithm or wavelet transform. In order to distinguish data in the two states, we performed classification by using Support Vector Machine (SVM) method. Results showed that SVM classifier was able to anticipate up to 78% of the movements executed.

Place, publisher, year, edition, pages
2012. Vol. 7, 157- p.
National Category
Computer Science Engineering and Technology
URN: urn:nbn:se:kth:diva-191563OAI: diva2:957395
FENS Forum, Barcelona, Spain

QC 20160902

Available from: 2016-09-01 Created: 2016-09-01 Last updated: 2016-09-02Bibliographically approved

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