Zobrazeno 1 - 10
of 131
pro vyhledávání: '"Zhuliang YU"'
Publikováno v:
IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol 32, Pp 1524-1534 (2024)
Electroencephalographic (EEG) source imaging (ESI) is a powerful method for studying brain functions and surgical resection of epileptic foci. However, accurately estimating the location and extent of brain sources remains challenging due to noise an
Externí odkaz:
https://doaj.org/article/3231f320b1b8444eb87393606997f3fb
Publikováno v:
IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol 31, Pp 3988-3998 (2023)
Motor imagery (MI) decoding plays a crucial role in the advancement of electroencephalography (EEG)-based brain-computer interface (BCI) technology. Currently, most researches focus on complex deep learning structures for MI decoding. The growing com
Externí odkaz:
https://doaj.org/article/7104c28fa6764c5f9b94959bea1b31c7
Autor:
Ronghua Ma, Hao Zhang, Jun Zhang, Xiaoli Zhong, Zhuliang Yu, Yuanqing Li, Tianyou Yu, Zhenghui Gu
Publikováno v:
IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol 31, Pp 2789-2799 (2023)
P300 potential is important to cognitive neuroscience research, and has also been widely applied in brain-computer interfaces (BCIs). To detect P300, many neural network models, including convolutional neural networks (CNNs), have achieved outstandin
Externí odkaz:
https://doaj.org/article/b14009dc90de4a5dbaa7b0b46b5db5fc
Autor:
Jun Xiao, Yanbin He, Tianyou Yu, Jiahui Pan, Qiuyou Xie, Caiyun Cao, Heyi Zheng, Weitian Huang, Zhenghui Gu, Zhuliang Yu, Yuanqing Li
Publikováno v:
IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol 30, Pp 1422-1432 (2022)
Behavioral assessment of sound localization in the Coma Recovery Scale-Revised (CRS-R) poses a significant challenge due to motor disability in patients with disorders of consciousness (DOC). Brain-computer interfaces (BCIs), which can directly detec
Externí odkaz:
https://doaj.org/article/7594a350193944afa0172c5fc510cfe1
Publikováno v:
IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol 30, Pp 2834-2844 (2022)
Reinforcement-learning (RL)-based brain-machine interfaces (BMIs) interpret dynamic neural activity into movement intention without patients’ real limb movements, which is promising for clinical applications. A movement task generally requires the
Externí odkaz:
https://doaj.org/article/b18162b52f044a58a0029a8ec7439097
Publikováno v:
Frontiers in Neurorobotics, Vol 16 (2022)
The electroencephalography (EEG) signals are easily contaminated by various artifacts and noise, which induces a domain shift in each subject and significant pattern variability among different subjects. Therefore, it hinders the improvement of EEG c
Externí odkaz:
https://doaj.org/article/a23427f1b19c427eb3b6f832a1351033
Publikováno v:
智能科学与技术学报, Vol 3, Pp 85-92 (2021)
As an active research direction in the field of neural engineering, brain-computer interface (BCI) has important research significance in biomedicine, neural rehabilitation, intelligent robot and other fields.The human-computer shared control technol
Externí odkaz:
https://doaj.org/article/0f15b4eff20444e4b9970b693b3d2b46
Publikováno v:
IEEE Transactions on Biomedical Engineering. 70:1879-1890
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3717ae7007a27220730a05aa51868bf8
https://doi.org/10.1109/tbme.2022.3231627
https://doi.org/10.1109/tbme.2022.3231627
Autor:
Qiyang Lu, Weiyuan Lin, Ruichen Zhang, Rui Chen, Xiaoyu Wei, Tingyu Li, Zhicheng Du, Zhaofeng Xie, Zhuliang Yu, Xinzhou Xie, Hui Liu
Publikováno v:
Frontiers in Neuroinformatics, Vol 14 (2020)
Purpose: The clinical diagnosis of aorta coarctation (CoA) constitutes a challenge, which is usually tackled by applying the peak systolic pressure gradient (PSPG) method. Recent advances in computational fluid dynamics (CFD) have suggested that mult
Externí odkaz:
https://doaj.org/article/91eedc9ccbb54b0c910706632ffbc920
Publikováno v:
BioMedical Engineering OnLine, Vol 17, Iss 1, Pp 1-12 (2018)
Abstract Background Hemodynamic information including peak systolic pressure (PSP) and peak systolic velocity (PSV) carry an important role in evaluation and diagnosis of congenital heart disease (CHD). Since MDCTA cannot evaluate hemodynamic informa
Externí odkaz:
https://doaj.org/article/3006bef359464aacbcfb1658e9a262c3