Subject-Specific Sinusoid Approach for A Brain–Computer Interface Based on Single-Channel Steady-State Visual Evoked Potential

Abdullah Talha Sözer

EN TR

Subject-Specific Sinusoid Approach for A Brain–Computer Interface Based on Single-Channel Steady-State Visual Evoked Potential

Öz

The aim of brain–computer interface (BCI) is to support the daily life of individuals with severe disabilities. For practical BCI, ease of use is one of the most important factors, which is enhanced when fewer electrodes are used. However, using fewer electrode affect the performance of BCI negatively. In this study, a novel single-channel steady-state visual evoked potential (SSVEP) detection method with subject-specific sinusoids approach (SSSA) was developed to enhance the performance of single channel SSVEP based BCI, therefore, to assist the ease of use. For the SSSA, subject-specific sinusoids were defined from training data based on SSVEP frequency and phase features. To detect the SSVEP response, defined sinusoids were used as reference. To evaluate the detection performance of the developed method, it was compared with the well-known power spectral density analysis (PSDA), least absolute shrinkage and selection operator (LASSO) and advanced canonical correlation analysis (CCA) methods on a benchmark dataset. The experimental results showed significantly greater detection accuracy and information transfer rate (ITR) with the SSSA method compared to the PSDA, LASSO and advanced CCA methods. And it is worth to noting that subject-specific sinusoids better represent SSVEP response than template signals that used in advanced CCA. Also proposed method reached one of the highest ITRs reported with max 125 and average 81 bits/min ITRs for single-channel SSVEP based BCI.

Anahtar Kelimeler

Brain Computer Interface, Steady-State Visual Evoked Potential, Single Channel Detection, Subject-Specific Sinusoid

Tek Kanallı Durağan Hal Görsel Uyandırılmış Potansiyel Temelli Beyin-Bilgisayar Arayüzü İçin Deneğe Özgü Sinüzoit Yaklaşımı

Öz

Beyin-bilgisayar arayüzünün (BBA) amacı, ciddi engelli bireylerin günlük yaşamlarını desteklemektir. Pratik BBA için en önemli faktörlerden biri olan kullanım kolaylığı, az sayıda elektrot kullanıldığında artmaktadır. Ancak az sayıda elektrot kullanılması BBA performansını olumsuz yönde etkiler. Bu çalışmada, tek kanallı durağan hal görsel uyarılmış potansiyel (DHGUP) temelli BBA’nın performansını artırmak ve böylece kullanım kolaylığını desteklemek için, deneğe özgü sinüzoit yaklaşımı (DÖSY) ile yeni bir tek kanallı DHGUP algılama yöntemi geliştirilmiştir. DÖSY’de deneğe özgü sinüzoitler, eğitim aşamasında DHGUP’nin frekans ve faz özelliklerinden faydalanılarak tanımlanmıştır. Tanımlanan bu sinüzoitler, test aşamasında, DHGUP yanıtının tespitinde referans olarak kullanılmıştır. Geliştirilen yöntemin tespit performansı, bir kıyaslama veri setinde, iyi bilinen güç spektral yoğunluk analizi (GSYA), minimum mutlak büzülme ve seçim operatörü (MMBSO) ve gelişmiş kanonik korelasyon analizi (KKA) yöntemleri ile karşılaştırılarak test edilmiştir. Deneysel sonuçlar, DÖSY yöntemiyle, GSYA, MMBSO ve gelişmiş KKA yöntemlerine kıyasla önemli ölçüde daha yüksek tespit doğruluğu ve bilgi aktarım hızı (BAH) göstermiştir. Ve deneğe özgü sinüzoitlerin gelişmiş KKA’da kullanılan şablon sinyallerden daha iyi DHGUP yanıtını temsil ettiği gösterilmiştir. Ek olarak önerilen yöntem, tek kanallı DHGUP tabanlı BBA için maksimum 125 ve ortalama 81 bit / dak BAH ile, bildirilen en yüksek BAH değerlerinden birine ulaşmıştır.

Anahtar Kelimeler

Beyin Bilgisayar Arayüzü, Durağan Hal Görsel Uyarılmış Potansiyel, Tek Kanal Tespit, Deneğe Özgü Sinüzoit

Kaynakça

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Ayrıntılar

Birincil Dil

İngilizce

Konular

Mühendislik

Bölüm

Araştırma Makalesi

Yazarlar

Abdullah Talha Sözer ^*
0000-0002-7855-6119
Türkiye

Yayımlanma Tarihi

30 Haziran 2021

Gönderilme Tarihi

17 Aralık 2020

Kabul Tarihi

24 Haziran 2021

Yayımlandığı Sayı

Yıl 2021 Cilt: 3 Sayı: 1

IZ

https://izlik.org/JA87PJ52XE

APA

Sözer, A. T. (2021). Subject-Specific Sinusoid Approach for A Brain–Computer Interface Based on Single-Channel Steady-State Visual Evoked Potential. Necmettin Erbakan University Journal of Science and Engineering, 3(1), 1-12. https://izlik.org/JA87PJ52XE

AMA

1.Sözer AT. Subject-Specific Sinusoid Approach for A Brain–Computer Interface Based on Single-Channel Steady-State Visual Evoked Potential. NEU Fen Muh Bil Der. 2021;3(1):1-12. https://izlik.org/JA87PJ52XE

Chicago

Sözer, Abdullah Talha. 2021. “Subject-Specific Sinusoid Approach for A Brain–Computer Interface Based on Single-Channel Steady-State Visual Evoked Potential”. Necmettin Erbakan University Journal of Science and Engineering 3 (1): 1-12. https://izlik.org/JA87PJ52XE.

EndNote

Sözer AT (01 Haziran 2021) Subject-Specific Sinusoid Approach for A Brain–Computer Interface Based on Single-Channel Steady-State Visual Evoked Potential. Necmettin Erbakan University Journal of Science and Engineering 3 1 1–12.

IEEE

[1]A. T. Sözer, “Subject-Specific Sinusoid Approach for A Brain–Computer Interface Based on Single-Channel Steady-State Visual Evoked Potential”, NEU Fen Muh Bil Der, c. 3, sy 1, ss. 1–12, Haz. 2021, [çevrimiçi]. Erişim adresi: https://izlik.org/JA87PJ52XE

ISNAD

Sözer, Abdullah Talha. “Subject-Specific Sinusoid Approach for A Brain–Computer Interface Based on Single-Channel Steady-State Visual Evoked Potential”. Necmettin Erbakan University Journal of Science and Engineering 3/1 (01 Haziran 2021): 1-12. https://izlik.org/JA87PJ52XE.

JAMA

1.Sözer AT. Subject-Specific Sinusoid Approach for A Brain–Computer Interface Based on Single-Channel Steady-State Visual Evoked Potential. NEU Fen Muh Bil Der. 2021;3:1–12.

MLA

Sözer, Abdullah Talha. “Subject-Specific Sinusoid Approach for A Brain–Computer Interface Based on Single-Channel Steady-State Visual Evoked Potential”. Necmettin Erbakan University Journal of Science and Engineering, c. 3, sy 1, Haziran 2021, ss. 1-12, https://izlik.org/JA87PJ52XE.

Vancouver

1.Abdullah Talha Sözer. Subject-Specific Sinusoid Approach for A Brain–Computer Interface Based on Single-Channel Steady-State Visual Evoked Potential. NEU Fen Muh Bil Der [Internet]. 01 Haziran 2021;3(1):1-12. Erişim adresi: https://izlik.org/JA87PJ52XE

Subject-Specific Sinusoid Approach for A Brain–Computer Interface Based on Single-Channel Steady-State Visual Evoked Potential

Öz

Anahtar Kelimeler

Tek Kanallı Durağan Hal Görsel Uyandırılmış Potansiyel Temelli Beyin-Bilgisayar Arayüzü İçin Deneğe Özgü Sinüzoit Yaklaşımı

Öz

Anahtar Kelimeler

Kaynakça

Ayrıntılar

Birincil Dil

Konular

Bölüm

Yazarlar

Yayımlanma Tarihi

Gönderilme Tarihi

Kabul Tarihi

Yayımlandığı Sayı

IZ

Kaynak Göster