A Review of Electroencephalography Brain-Machine Interfaces of Dynamic Modeling

Yıl 2020, Cilt: 13 Sayı: 2, 1 - 16, 16.12.2020

Zehra Yıldız

Öz

The rapid development of neural activity imaging and analysis techniques in neuroscience in recent years has helped us to understand how information is processed in neural networks in the brain. Thanks to the new approaches and developments related to the organization and functioning of neural networks, medical neurological conditions that seem impossible to solve can be treated, and radical new communication systems and medical prostheses can be made that can improve the quality of life for thousands of people with motor and communication deficiencies. Brain-Machine or Brain-Computer Interfaces (BBA) is a new field of research that has made rapid progress in the last 10-15 years. Noninvasive electroencephalography (EEG) imaging, functional magnetic resonance imaging, and visual memory of subjects were found to be successful. Since statistical neural activity dynamic models have been successful in the analysis and interpretation of neural activity in the brain in basic neuroscience, this study focused on the dynamic modeling used in EEG BBA neural activity data. In the future, both in the international arena with the study of health used in Turkey, civilian and military applications with walking prosthesis, decision making systems or semi-automatic robot and help to control devices such as camera systems or provides high-level control of complete BBA solution developed in Turkey to will contribute.

Anahtar Kelimeler

Brain-computer interface, electroencephalography, neuroprosthetics, neuroimaging, machine learning, computational neuroscience, scientific computing

Elektroensefalografi Beyin-Makine Arayüzlerin Modellemesi

Öz

Nörobilimdeki nöral aktivite görüntüleme ve analiz tekniklerinin son yıllarda hızlı gelişimi, bilginin beyindeki sinir ağlarında nasıl işlendiğini anlamamıza yardımcı olmuştur. Sinir ağlarının düzeni ve işleyişi hakkında elde edilen yeni yaklaşımlar ve bunlara bağlı gelişmeler sayesinde çözümlenmesi imkansız gibi görünen tıbbi nörolojik durumlar tedavi edilebilecek, motor ve iletişim yetersizliği olan binlerce insan için hayat kalitesini iyileştirebilecek radikal yeni iletişim sistemleri ve tıbbi protezler yapılabilecektir. Beyin-Makine ya da Beyin-Bilgisayar Arayüzleri (BBA) son 10-15 yılda hızlı ilerlemeler kaydeden yeni bir araştırma alanıdır. Noninvaziv elektroensefalografi (EEG) görüntüleme, fonksiyonel manyetik rezonans görüntüleme, deneklerin görsel hafızaları üzerinde başarılı sonuçlar verebileceği görülmüştür. Bu çalışmada, EEG beyin aktivite görüntüleme tekniğini kullanan BBA sistemlerinin pratik uygulamaları ve etkinliğini artırmak için için verimli istatistiksel nöral veri analiz teknikleri ve BBA deneysel tasarımları incelenmiştir. İstatistiksel nöral aktivite dinamik modelleri, temel nörobilimde beyindeki nöral aktivite analizi ve yorumlanmasında son yıllarda başarılı olduğundan bu çalışmada EEG BBA nöral aktivite verilerin kullanan dinamik modelleme üzerinde yoğunlaşılmıştır. Bu çalışma hem uluslararası alanda hem de Türkiye’de kullanılan sağlık, sivil ve askeri uygulamalar ile yürüme protezleri, karar verme sistemleri veya yarı otomatik robot ve makine sistemleri gibi cihazların kontrolüne yardımcı veya yüksek seviye kontrolü sağlayan komple BBA çözümlerinin Türkiye’de geliştirilmesine katkıda bulunacaktır.

Anahtar Kelimeler

elektroensefalografi, Beyin-bilgisayar arayüzeyi, sinirsel protezler, makine öğrenme, bilgisayarlı nörobilim

Kaynakça

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