Improved Accuracy for Subject-Dependent and Subject-Independent Deep Learning-Based SSVEP BCI Classification: A User-Friendly Approach

In the brain-computer interface, the SSVEP (steady-state visual evoked potential) method serves to foster collaboration between humans and robots. SSVEP-based detection methods require complex multichannel data acquisition, making them difficult to deploy due to discomfort during extended use and th...

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Detaylı Bibliyografya
Asıl Yazarlar:	Adeel Wahab, Umar Shahbaz Khan, Tahir Nawaz, Hassan Akbar, Syed Tayyab Hussain Shah, Azfar Khalid, Ali R. Ansari, Raheel Nawaz
Materyal Türü:	Artigo
Dil:	Inglês
Baskı/Yayın Bilgisi:	IEEE 2024-01-01
Seri Bilgileri:	IEEE Access
Konular:	Steady-state visual evoked potential single-channel human-robot collaboration deep neural network variational mode decomposition EEG measurement and classification technique
Online Erişim:	https://ieeexplore.ieee.org/document/10634158/
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Improved Accuracy for Subject-Dependent and Subject-Independent Deep Learning-Based SSVEP BCI Classification: A User-Friendly Approach

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