Zobrazeno 1 - 10
of 21
pro vyhledávání: '"Hongjian Bo"'
Publikováno v:
Frontiers in Computational Neuroscience, Vol 18 (2024)
Epilepsy is a common chronic brain disorder. Detecting epilepsy by observing electroencephalography (EEG) is the main method neurologists use, but this method is time-consuming. EEG signals are non-stationary, nonlinear, and often highly noisy, so it
Externí odkaz:
https://doaj.org/article/e14be28d96fe47efa05b6e0acbe29628
Autor:
Wenhao Jiang, Shihang Ding, Cong Xu, Huihuang Ke, Hongjian Bo, Tiejun Zhao, Lin Ma, Haifeng Li
Publikováno v:
Frontiers in Human Neuroscience, Vol 17 (2023)
IntroductionMajor Depressive Disorder (MDD) is a leading cause of worldwide disability, and standard clinical treatments have limitations due to the absence of neurological evidence. Electroencephalography (EEG) monitoring is an effective method for
Externí odkaz:
https://doaj.org/article/a94e9375420242a19bd8c35877df22b6
Publikováno v:
Frontiers in Neuroscience, Vol 15 (2021)
Recently, emotion classification from electroencephalogram (EEG) data has attracted much attention. As EEG is an unsteady and rapidly changing voltage signal, the features extracted from EEG usually change dramatically, whereas emotion states change
Externí odkaz:
https://doaj.org/article/da6ee83eb4344ae29f4c41a75066c8de
Publikováno v:
Algorithms, Vol 14, Iss 9, p 271 (2021)
At present, there are very few analysis methods for long-term electroencephalogram (EEG) components. Temporal information is always ignored by most of the existing techniques in cognitive studies. Therefore, a new analysis method based on time-varyin
Externí odkaz:
https://doaj.org/article/6b56eacc9d8c4f0db0751979e7b64d3c
Publikováno v:
IEEE Transactions on Pattern Analysis and Machine Intelligence. 44:9417-9433
Deep neural networks have achieved great success in almost every field of artificial intelligence. However, several weaknesses keep bothering researchers due to its hierarchical structure, particularly when large-scale parallelism, faster learning, b
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f038933676674e00a8eaa7b7c1f220bb
https://doi.org/10.1109/tpami.2021.3125690
https://doi.org/10.1109/tpami.2021.3125690
Publikováno v:
2022 IEEE International Conference on Multimedia and Expo Workshops (ICMEW).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1c7eff13e803926d0a8741fcd297b40f
https://doi.org/10.1109/icmew56448.2022.9859269
https://doi.org/10.1109/icmew56448.2022.9859269
Publikováno v:
MIPR
For centuries, music has been an important part of various cultures and a special language for humans to express their thoughts and emotions. Music emotion plays an important role in music retrieval, mood detection and other music-related application
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::998b04956acdb9767eda8c8a937ee6f3
https://doi.org/10.1109/mipr51284.2021.00066
https://doi.org/10.1109/mipr51284.2021.00066
Publikováno v:
Algorithms, Vol 14, Iss 271, p 271 (2021)
Algorithms; Volume 14; Issue 9; Pages: 271
Algorithms; Volume 14; Issue 9; Pages: 271
At present, there are very few analysis methods for long-term electroencephalogram (EEG) components. Temporal information is always ignored by most of the existing techniques in cognitive studies. Therefore, a new analysis method based on time-varyin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::146d58a95dc3c8696d7918f0ca23671a
https://www.mdpi.com/1999-4893/14/9/271
https://www.mdpi.com/1999-4893/14/9/271
Autor:
Xiaojing, Lin, Hongjian, Bo, Jia, Gu, Xueqing, Yi, Peng, Zhang, Ruoxu, Liu, Haifeng, Li, Gang, Sun, Cheng-Hsien, Lin
Publikováno v:
Biomedicine & Pharmacotherapy. 148:112777
We first explore whether aircraft noise (AN) induces cognitive deficit via inducing oxidative damage in multiple vital organs including intestines, hearts and hippocampus tissues. Second, we explore whether the AN-induced cognitive deficits and infla
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e8b6e5da7cedfb14baf1717d75bcd845
https://doi.org/10.1016/j.biopha.2022.112777
https://doi.org/10.1016/j.biopha.2022.112777
Publikováno v:
MIPR
Electroencephalograph (EEG) is widely used to study human brain activities. However, the interpretation of EEG signals is still a challenging computational task. Emerging evidence has shown that the non-stationary traits of EEG signals hinder the way
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::882f392377f5e424a530d18b559afa14
https://doi.org/10.1109/mipr49039.2020.00082
https://doi.org/10.1109/mipr49039.2020.00082