Design and development of an SSVEP based low cost, wearable, and wireless BCI system

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buir.advisorIder, Yusuf Ziya
dc.contributor.authorWaheed, Abdul
dc.date.accessioned2019-08-19T08:08:29Z
dc.date.available2019-08-19T08:08:29Z
dc.date.copyright2019-08
dc.date.issued2019-08
dc.date.submitted2019-08-16
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.descriptionCataloged from PDF version of article.en_US
dc.descriptionThesis (M.S.): Bilkent University, Department of Electrical and Electronics Engineering, İhsan Doğramacı Bilkent University, 2019.en_US
dc.descriptionIncludes bibliographical references (leaves 82-92).en_US
dc.description.abstractIt has become a challenging research topic to design and develop cheap and wearable brain-computer interface (BCI) systems but not compromising the performance. In this thesis, the design and development of a steady state visually evoked potential (SSVEP) based BCI system has been presented which is a low cost, wearable BCI system and gives highly accurate target identi cations with good information transfer rate (ITR). It is a battery powered, wireless BCI system and ensures the complete isolation to the subject. Like all the BCI systems, it is designed and implemented in ve major parts: (i) stimulator which is a microcontroller based circuit and provides the frequency modulated visually evoked potential (f-VEP) and code-modulated visually evoked potential (c-VEP) stimulations (ii) dry active electrodes which capture the electroencephalography(EEG) signals from the O1, O2, and Oz head positions (iii) high sampling rate, 4-channel EEG data acquisition hardware which acquires the EEG signals, amplify them, converts them to digital data, and transmits the data using wi communication (iv) the data processing unit (DPU) which is a MATLAB script to process the raw EEG data and displays the results and (v) the headset which mounts all the components except DPU and is developed using 3D printing technology. The rst prototype of the proposed BCI system has been developed in 331 USD and tested for both the f-VEP and c-VEP modalities on six human subjects. For f-VEP modality, it exhibits an average accuracy (live accuracy) of 92.1% and average ITR (live ITR) of 69.5 bits/min on the basis of target identi cations done on 1:04 s data recordings. If we extract one message character from ve consecutive target identi cations, the average message accuracy goes to 98.8% and average message ITR to 17.2 bits/min. In case of c-VEP modality, it exhibits live accuracy of 70.1 % and live ITR of 23.5 bits/min while message accuracy of 90.7 % and message ITR of 12.4 bit/min.en_US
dc.description.degreeM.S.en_US
dc.description.statementofresponsibilityby Abdul Waheeden_US
dc.format.extentxviii, 99 leaves : charts (some color) ; 30 cm.en_US
dc.identifier.itemidB111677
dc.identifier.urihttp://hdl.handle.net/11693/52348
dc.language.isoEnglishen_US
dc.publisherBilkent Universityen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectBCI systemen_US
dc.subjectSSVEPen_US
dc.subjectLow costen_US
dc.subjectWearableen_US
dc.subjectWirelessen_US
dc.titleDesign and development of an SSVEP based low cost, wearable, and wireless BCI systemen_US
dc.title.alternativeDHGUP bazlı ucuz ve giyilebilir bir telsiz BBA sisteminin tasarım ve geliştirilmesien_US
dc.typeThesisen_US
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