Zobrazeno 1 - 10
of 62
pro vyhledávání: '"Yufeng Ke"'
Publikováno v:
IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol 32, Pp 1407-1415 (2024)
Steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs) have emerged as a prominent technology due to their high information transfer rate, rapid calibration time, and robust signal-to-noise ratio. However, a critical chal
Externí odkaz:
https://doaj.org/article/81346f4280b64706a3848f1de3b37fe8
Publikováno v:
npj Science of Learning, Vol 8, Iss 1, Pp 1-13 (2023)
Abstract The neural basis for long-term behavioral improvements resulting from multi-session transcranial direct current stimulation (tDCS) combined with working memory training (WMT) remains unclear. In this study, we used task-related electroenceph
Externí odkaz:
https://doaj.org/article/bfaae03013b347aa87575803c794c9b8
Publikováno v:
IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol 31, Pp 1405-1417 (2023)
This study proposed a novel frequency-specific (FS) algorithm framework for enhancing control state detection using short data length toward high-performance asynchronous steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (B
Externí odkaz:
https://doaj.org/article/3f0eb4dc0aa64f3d9f0ec81475650d4c
Publikováno v:
Frontiers in Neuroscience, Vol 17 (2023)
Neuronal oscillations are the primary basis for precise temporal coordination of neuronal processing and are linked to different brain functions. Transcranial alternating current stimulation (tACS) has demonstrated promising potential in improving co
Externí odkaz:
https://doaj.org/article/98b9e1d2a5c64b069acdd9b2a2de0875
Publikováno v:
Frontiers in Neuroscience, Vol 16 (2022)
Research in the cognitive neuroscience field has shown that individuals with a stronger attention bias for negative information had higher depression risk, which may be the underlying pathogenesis of depression. This dysfunction of affect-biased atte
Externí odkaz:
https://doaj.org/article/c209999cddb241ae85d3cc13513d85c6
Publikováno v:
Frontiers in Neuroscience, Vol 15 (2021)
Mental workload (MWL) estimators based on ongoing electroencephalography (EEG) and event-related potentials (ERPs) have shown great potentials to build adaptive aiding systems for human–machine systems by estimating MWL in real time. However, extra
Externí odkaz:
https://doaj.org/article/c71fb4659d5a4184a2681b9da0912361
Publikováno v:
Frontiers in Neuroscience, Vol 15 (2021)
ObjectiveCollaborative brain–computer interfaces (cBCIs) can make the BCI output more credible by jointly decoding concurrent brain signals from multiple collaborators. Current cBCI systems usually require all collaborators to execute the same ment
Externí odkaz:
https://doaj.org/article/01ad33146bfa42ca897bd43166799e60
Publikováno v:
IEEE Access, Vol 7, Pp 42113-42122 (2019)
The brain activity pattern can be presented by Electroencephalogram (EEG), which is considered as an alternative to traditional biometrics. Researchers have done conducted studies on EEG-based identification, while few of them discussed the effect of
Externí odkaz:
https://doaj.org/article/1588714f16c04b369562b611d7cbccfc
Publikováno v:
Frontiers in Human Neuroscience, Vol 14 (2020)
Cross-subject variability problems hinder practical usages of Brain-Computer Interfaces. Recently, deep learning has been introduced into the BCI community due to its better generalization and feature representation abilities. However, most studies c
Externí odkaz:
https://doaj.org/article/2a6d0e9a2f1a403e8524c9e093767aff
Autor:
Yong Cao, Xingwei An, Yufeng Ke, Jin Jiang, Hanjun Yang, Yuqian Chen, Xuejun Jiao, Hongzhi Qi, Dong Ming
Publikováno v:
BioMedical Engineering OnLine, Vol 16, Iss 1, Pp 1-14 (2017)
Abstract Background Over the past few decades, there have been many studies of aspects of brain–computer interface (BCI). Of particular interests are event-related potential (ERP)-based BCI spellers that aim at helping mental typewriting. Nowadays,
Externí odkaz:
https://doaj.org/article/48fea22367b74119bb3ac64168e3b549