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Considering preferences, speed and the animation of multiple symbols in developing P300 brain-computer interface for children.

Autor: Pitt KM; Department of Special Education and Communication Disorders, University of NE-Lincoln, Lincoln, NE, USA., Spoor A; Department of Special Education and Communication Disorders, University of NE-Lincoln, Lincoln, NE, USA., Zosky J; Department of Psychology, University of Nebraska-Lincoln, Lincoln, NE, USA.

Publikováno v: Disability and rehabilitation. Assistive technology [Disabil Rehabil Assist Technol] 2025 Jan; Vol. 20 (1), pp. 171-183. Date of Electronic Publication: 2024 May 29.

Subject-Independent Wearable P300 Brain–Computer Interface Based on Convolutional Neural Network and Metric Learning

Autor: Li Hu, Wei Gao, Zilin Lu, Chun Shan, Haiwei Ma, Wenyu Zhang, Yuanqing Li

Publikováno v: IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol 32, Pp 3543-3553 (2024)

The calibration procedure for a wearable P300 brain-computer interface (BCI) greatly impact the user experience of the system. Each user needs to spend additional time establishing a decoder adapted to their own brainwaves. Therefore, achieving subje

Externí odkaz: https://doaj.org/article/0ab31a6a94cb47008f340950df0f4600

Brain Invaders Adaptive versus Non-Adaptive P300 Brain-Computer Interface dataset

Autor: Vaineau, Erwan, Barachant, Alexandre, Andreev, Anton, Rodrigues, Pedro C., Cattan, Grégoire, Congedo, Marco

We describe the experimental procedures for a dataset that we have made publicly available at https://doi.org/10.5281/zenodo.1494163 in mat and csv formats. This dataset contains electroencephalographic (EEG) recordings of 24 subjects doing a visual

Externí odkaz: http://arxiv.org/abs/1904.09111