Zobrazeno 1 - 10
of 352
pro vyhledávání: '"Honglin, Hu"'
Publikováno v:
Frontiers in Neuroscience, Vol 18 (2024)
ObjectiveThe brain-computer interface (BCI) systems based on rapid serial visual presentation (RSVP) have been widely utilized for the detection of target and non-target images. Collaborative brain-computer interface (cBCI) effectively fuses electroe
Externí odkaz:
https://doaj.org/article/cc5d9c1b46ce4818b72f1f98aa98c246
Publikováno v:
IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol 32, Pp 1687-1702 (2024)
As an essential cognitive function, attention has been widely studied and various indices based on EEG have been proposed for its convenience and easy availability for real-time attention monitoring. Although existing indices based on spectral power
Externí odkaz:
https://doaj.org/article/28851dbf93744ecd8579654ad3d3fa53
Autor:
Xuelin Yao, Keyan Hu, Zhen Wang, Fangting Lu, Jie Zhang, Yahu Miao, Qing Feng, Tian Jiang, Yi Zhang, Songtao Tang, Nan Zhang, Fang Dai, Honglin Hu, Qiu Zhang, the China National Diabetic Chronic Complications Study Group
Publikováno v:
Diabetology & Metabolic Syndrome, Vol 16, Iss 1, Pp 1-10 (2024)
Abstract Background Body mass index (BMI) is an important risk factor for hypertension in diabetic patients. However, the underlying mechanisms remain poorly understood. Although liver-derived biological intermediates may play irreplaceable roles in
Externí odkaz:
https://doaj.org/article/0a632368dcc242119c22bfc77d2c4245
Autor:
Xing Wang, Ruizhen Huang, Juhui Yu, Fei Zhu, Xiaoqing Xi, Yawei Huang, Chiyu Zhang, Honglin Hu
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-12 (2023)
Abstract Circular RNAs (circRNAs) are linked to cancer, but it's still not clear what role they play in prostatic cancer. Through high-throughput sequencing, the goal of this study was to compare how circRNAs are expressed at different stages of pros
Externí odkaz:
https://doaj.org/article/0d8c02406b804b3db1628b41324f9781
Publikováno v:
Pharmaceutical Biology, Vol 61, Iss 1, Pp 306-315 (2023)
AbstractContext Sepsis is a systemic inflammatory response caused by infection, with high morbidity and mortality. Omega-3 polyunsaturated fatty acids (ω-3 PUFAs) have reported biological activities.Objective This study explored the signaling pathwa
Externí odkaz:
https://doaj.org/article/88de399ed6ff4207b634a5c9a3d8481c
Publikováno v:
Frontiers in Neuroscience, Vol 18 (2024)
Steady-state visual evoked potential brain-computer interfaces (SSVEP-BCI) have attracted significant attention due to their ease of deployment and high performance in terms of information transfer rate (ITR) and accuracy, making them a promising can
Externí odkaz:
https://doaj.org/article/0da69a2bfa5040f7a9860309ede8fc28
Autor:
Shibin Yao, Wenjian Li, Chunfang Cai, Chengrui Wang, Jia Kang, Honglin Hu, Ping Wu, Xiamin Cao, Yuantu Ye
Publikováno v:
Aquaculture Nutrition, Vol 2024 (2024)
The effects of plant protein sources (PPSs) on the health of the liver and intestine of the largemouth bass, Micropterus salmoides, were compared to verify the potential damaging effects of dietary fiber (DF). A diet containing 55% fish meal (FM) was
Externí odkaz:
https://doaj.org/article/678569c468454e4eac59f7fa84265763
Publikováno v:
IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol 31, Pp 4760-4772 (2023)
Traditional single-modality brain-computer interface (BCI) systems are limited by their reliance on a single characteristic of brain signals. To address this issue, incorporating multiple features from EEG signals can provide robust information to en
Externí odkaz:
https://doaj.org/article/e0f29adac676401b9b0e96f596943917
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
Publikováno v:
IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol 31, Pp 1743-1753 (2023)
In recent years, deep neural network-based transfer learning (TL) has shown outstanding performance in EEG-based motor imagery (MI) brain-computer interface (BCI). However, due to the long preparation for pre-trained models and the arbitrariness of s
Externí odkaz:
https://doaj.org/article/5ecfb0db09524d319319e8ad36b28e22