Gerçek ve Hayali Kol Hareketlerine ait EEG verilerinin Spektral Koherens Yöntemiyle Analizi

Abstract

Gerçek bir motor görev ve onun hayal edilmesi arasındaki benzer aktivasyon örüntülerinin tanımlanması, beyindeki hareket niyet noktalarının tespit edilmesine ve Beyin Bilgisayar Arayüzlerinin (BBA) geliştirilmesine yardımcı olabilir. Bu çalışmada, gerçek ve hayali bir kol hareketi görevi yapan nöral bölgeler arasındaki fonksiyonel etkileşimler, spektral koherens yöntemi ile değerlendirilmiştir. Çift kat güçlendirilmiş koherens değerleri, tipik alfa (8-12 Hz) ve beta (13-20 Hz) frekans bant aralığında seçilen ilişkili bölgedeki (İB) 48 farklı Elektroensefalogram (EEG) kanalı için hesaplanmıştır. Farklı görevler için hesaplanan koherens değerleri, yüzey haritalarına dönüştürülmüştür. Bu bölgelerdeki motor biliş anlayışımızın sağ ve sol kol ile ilgili literatürden elde edilen bulgularla nasıl ilişkili olduğu açıklanmaya çalışılmıştır. Aynı yarımküredeki kanallar ile 10-20 elektrot yerleşimi temelinde dikey ve yatay olarak yerleştirilmiş en yakın kanallar arasında maksimum tutarlılığın gözlendiği gösterilmiştir. Çalışmamızın sonuçları, literatürde yer alan tamamlayıcı motor alanının, premotor, prefrontal ve primer motor kortekslerinin ve parietal korteksin gerçek ve hayali motor hareketlerini kolaylaştırmada rol oynadığı bulguları ile uyumludur. Çalışmanın sonuçları, spektral tutarlılık modellerinin protez-etkileşimli BBA sistemleri, etkileşimli multimedya uygulamaları ve ortaya çıkan EEG tabanlı biyometrik tanıma alanları için olası bir araç olabileceğini göstermektedir. 

Keywords

• EEG
• Spektral koherens
• BBA
• Motor görev sınıflandırma
• Gerçek ve hayali kol hareketleri

EEG ANALYSIS OF REAL AND IMAGINARY ARM MOVEMENTS BY SPECTRAL COHERENCE

Abstract

Revealing the information between similar patterns of brain for a real motor task and its imaginary equivalent can be means to clarify movement intentions and help to improve Brain Computer Interfaces (BCI)s. This paper uses spectral coherence to assess the functional interactions between neural regions engaged in a real and an imagined arm movement task. Magnitude squared coherence values were calculated for two specific bands of Electroencephalogram (EEG) that are 8–12 Hz alpha band and 13–20 Hz beta for 48 channels from selected regions of interest (ROIs). The coherence values are transferred into surface maps. We try to explain how motor cognition in these regions are relevant with the literature. The maximum coherence is observed between the channels in the same hemisphere and surrounding closest channels located vertically and horizontally based on the 10-20 electrode placement. Our results that the supplementary motor area, the premotor, prefrontal, primary motor cortex and the parietal cortex play a role in facilitating real and imaginary motor movements, are in good accordance with the previous studies. Further research can be put on spectral coherence patterns which would be a possible means for prosthetic-interactive BCI systems, interactive multimedia applications, and emerging EEGbased biometric recognition areas.

Keywords

• EEG
• Spectral coherence
• BCI
• Motor task classification
• Real and imaginary arm movements

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