Zobrazeno 1 - 10
of 475
pro vyhledávání: '"Brain-Computer Interfaces (BCI)"'
Publikováno v:
Cogent Arts & Humanities, Vol 11, Iss 1 (2024)
Brain-computer interfaces (BCI) and neurolinguistics have become vital areas of scientific inquiry, focusing on neural mechanisms in language acquisition. While studies have examined brain activity during language learning, there’s a need for valid
Externí odkaz:
https://doaj.org/article/4f682337c19645d4b81e34a4f19d8452
Publikováno v:
Brazilian Archives of Biology and Technology, Vol 67 (2024)
Abstract Motor imaging (MI) has been commonly employed in the domains of nervous analysis and robot control as an essential model of impulsive brain-computer interfaces (BCIs). Several approaches for extraction and classification based on MI signals
Externí odkaz:
https://doaj.org/article/8467e8ff45754282b5b36cff3ac6a87f
Autor:
Nour El Houda Sayah Ben Aissa, Ahmed Korichi, Abderrahmane Lakas, Chaker Abdelaziz Kerrache, Carlos T. Calafate
Publikováno v:
SLAS Technology, Vol 29, Iss 4, Pp 100142- (2024)
The classification of motor imagery (MI) using Electroencephalography (EEG) plays a pivotal role in facilitating communication for individuals with physical limitations through Brain-Computer Interface (BCI) systems. Recent strides in Attention-Based
Externí odkaz:
https://doaj.org/article/8729b19812354d208f42ced831fb3778
Publikováno v:
Frontiers in Human Neuroscience, Vol 18 (2024)
Externí odkaz:
https://doaj.org/article/4c55a0e685224bbeb8b9f9fc89715901
Publikováno v:
NeuroImage, Vol 297, Iss , Pp 120727- (2024)
This study investigates the complex relationship between upper limb movement direction and macroscopic neural signals in the brain, which is critical for understanding brain-computer interfaces (BCI). Conventional BCI research has primarily focused o
Externí odkaz:
https://doaj.org/article/925bc8cf55e24f4b80910bfa264fa3b8
Autor:
Cornelia Herbert, Georg Northoff
Publikováno v:
Frontiers in Human Neuroscience, Vol 18 (2024)
Externí odkaz:
https://doaj.org/article/8d6fee5e63c74b7aa5edb309353dbc33
Publikováno v:
IEEE Access, Vol 12, Pp 85969-85982 (2024)
Time-series classification (TSC) has been widely utilized across various domains, including brain-computer interfaces (BCI) for emotion recognition through electroencephalogram (EEG) signals. However, traditional methods often struggle to capture the
Externí odkaz:
https://doaj.org/article/418c9c0d9ac8460ba2b3164cc727f82e
Autor:
Donghyun Park, Hoonseok Park, Sangyeon Kim, Sanghyun Choo, Sangwon Lee, Chang S. Nam, Jae-Yoon Jung
Publikováno v:
IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol 31, Pp 4504-4513 (2023)
Recently, convolutional neural network (CNN)-based classification models have shown good performance for motor imagery (MI) brain-computer interfaces (BCI) using electroencephalogram (EEG) in end-to-end learning. Although a few explainable artificial
Externí odkaz:
https://doaj.org/article/67bb69bd6ee84fdf8019d21f6fba7599
Publikováno v:
IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol 31, Pp 4402-4412 (2023)
As a significant aspect of cognition, attention has been extensively studied and numerous measurements have been developed based on brain signal processing. Although existing attentional state classification methods have achieved good accuracy by ext
Externí odkaz:
https://doaj.org/article/cf326abccb854d91beb27204730e39f9
Autor:
Sonja C. Kleih-Dahms, Loic Botrel
Publikováno v:
Frontiers in Human Neuroscience, Vol 17 (2023)
IntroductionWe investigated a slow-cortical potential (SCP) neurofeedback therapy approach for rehabilitating chronic attention deficits after stroke. This study is the first attempt to train patients who survived stroke with SCP neurofeedback therap
Externí odkaz:
https://doaj.org/article/16598e8b84224d62946865dc3459663e