رسالة جامعية

Feature extraction and classification for motor imagery in EEG signals ; Numanomų motorikos požymių išskyrimas ir klasifikavimas elektroencefalografiniuose signaluose

التفاصيل البيبلوغرافية
العنوان: Feature extraction and classification for motor imagery in EEG signals ; Numanomų motorikos požymių išskyrimas ir klasifikavimas elektroencefalografiniuose signaluose
المؤلفون: Prasad, Aravind
المساهمون: Marozas, Vaidotas
بيانات النشر: Institutional Repository of Kaunas University of Technology
سنة النشر: 2018
المجموعة: LSRC VL (Lithuanian Social Research Centre Virtual Library) / LSTC VB (Lietuvos socialinių tyrimų centras virtualią biblioteką)
مصطلحات موضوعية: EEG, BCIi, Hjorth, LDA, motor imagery
الوصف: Electroencephalography is a non-invasive technique which is used for recording the neurophysiological reactions in the brain. It measures the activity of neurons. This report consists of different steps taken for finding that it is possible to control bionic arm with imaginary data of motor movement. The electroencephalographic signals were obtained from Physionet biosignal database. Feature extraction and its analysis is done for ten subjects. The different features were calculated for different segments of the obtained signal. The features extracted were inspired by Hjorth parameters and a higher order statistics - kurtosis. The signal processing algorithm for the process is explained in the report. The supervised feature classification is implemented using the Linear Discriminant Analysis. The obtained accuracy for the classifier was found to be around 60-70% depending on the electrodes and type of data (real or imaginary).
نوع الوثيقة: master thesis
وصف الملف: application/pdf
اللغة: Lithuanian
English
العلاقة: http://ktu.oai.elaba.lt/documents/16226672.pdfTest; http://ktu.lvb.lt/KTU:ELABAETD16226672&prefLang=en_USTest
الإتاحة: http://ktu.oai.elaba.lt/documents/16226672.pdfTest
http://ktu.lvb.lt/KTU:ELABAETD16226672&prefLang=en_USTest
حقوق: info:eu-repo/semantics/embargoedAccess
رقم الانضمام: edsbas.62D269E8
قاعدة البيانات: BASE