[HTML][HTML] One dimensional convolutional neural networks for seizure onset detection using long-term scalp and intracranial EEG
Epileptic seizure detection using scalp electroencephalogram (sEEG) and intracranial
electroencephalogram (iEEG) has attracted widespread attention in recent two decades …
electroencephalogram (iEEG) has attracted widespread attention in recent two decades …
Cross-domain EEG signal classification via geometric preserving transfer discriminative dictionary learning
X Gu, Z Shen, J Qu, T Ni - Multimedia Tools and Applications, 2022 - Springer
EEG signal classification is a key technology for EEG signal processing and identification
systems. Dictionary learning has shown excellent performance due to its sparse …
systems. Dictionary learning has shown excellent performance due to its sparse …
Empirical wavelet transform-based framework for diagnosis of epilepsy using EEG signals
SI Khan, RB Pachori - AI-enabled smart healthcare using biomedical …, 2022 - igi-global.com
In the chapter, a novel yet simple method for classifying EEG signals associated with normal
and epileptic seizure categories has been proposed. The proposed method is based on …
and epileptic seizure categories has been proposed. The proposed method is based on …
Evolving deep learning models for epilepsy diagnosis in data scarcity context: A survey
Recently, Epilepsy disorder has increasingly affected a large number of people worldwide,
and it is a complex neurological condition characterized as recurrent, involuntary …
and it is a complex neurological condition characterized as recurrent, involuntary …
Multifeature metric learning based on enhanced equidistance embedding for electroencephalogram recognition of epilepsy
B Lu, H Lu, G Zhou, X Yin, X Gu… - … and Mobile Computing, 2021 - Wiley Online Library
Mobile edge computing (MEC) has the ability of pattern recognition and intelligent
processing of real‐time data. Electroencephalogram (EEG) is a very important tool in the …
processing of real‐time data. Electroencephalogram (EEG) is a very important tool in the …
Construction of psychological warning mechanism for college students in big data environment
X HE, F CHEN - Chinese Journal of Medical Education …, 2021 - pesquisa.bvsalud.org
Combining the psychological" big data" of college students with the data of the
psychological expert database, using data mining algorithm to extract characteristic …
psychological expert database, using data mining algorithm to extract characteristic …
News Communication Value Evaluation Algorithm Based on Deep Neural Network
D Zhang - Wireless Communications and Mobile Computing, 2022 - Wiley Online Library
The evaluation of the value of news communication is an area that deserves more attention,
but there has been a dearth of specific research in this area. We must first determine the …
but there has been a dearth of specific research in this area. We must first determine the …
[HTML][HTML] Metric Learning in Freewill EEG Pre-Movement and Movement Intention Classification for Brain Machine Interfaces
W Plucknett, LG Sanchez Giraldo, J Bae - Frontiers in Human …, 2022 - frontiersin.org
Decoding movement related intentions is a key step to implement BMIs. Decoding EEG has
been challenging due to its low spatial resolution and signal to noise ratio. Metric learning …
been challenging due to its low spatial resolution and signal to noise ratio. Metric learning …
Psychological Health Assessment Model of Enterprise Employees Based on DNN Technology
X Li - Wireless Communications and Mobile Computing, 2022 - Wiley Online Library
All enterprises gradually recognise the importance of employees' healthy psychology to
business activities in order to improve their own economic level and occupy a certain …
business activities in order to improve their own economic level and occupy a certain …