Graph signal processing based cross-subject mental task classification using multi-channel EEG signals
Classification of mental tasks from electroencephalogram (EEG) signals play a crucial role in
designing various brain-computer interface (BCI) applications. Most of the current …
designing various brain-computer interface (BCI) applications. Most of the current …
Deep neural network for eeg signal-based subject-independent imaginary mental task classification
BACKGROUND. Mental task identification using electroencephalography (EEG) signals is
required for patients with limited or no motor movements. A subject-independent mental task …
required for patients with limited or no motor movements. A subject-independent mental task …
Discriminatory features based on wavelet energy for effective analysis of electroencephalogram during mental tasks
Mental task categorization using single/limited channel (s) electroencephalogram (EEG)
signals is crucial for designing portable brain–computer interface and neurofeedback …
signals is crucial for designing portable brain–computer interface and neurofeedback …
An Ensemble Approach to Classify Mental Stress using EEG Based Time-Frequency and Non-Linear Features
SS Swapnil, M Nuhi-Alamin… - … on Advancement in …, 2024 - ieeexplore.ieee.org
This study proposes a novel method for classifying mental stress before and during
arithmetic task using combined nonlinear features and time-frequency domain features …
arithmetic task using combined nonlinear features and time-frequency domain features …
Graph Signal Processing Based Cross-Subject Mental Task Classification Using Multi-Channel EEG Signals
VK Chakka - Authorea Preprints, 2023 - techrxiv.org
Classification of mental tasks from electroencephalogram (EEG) signals play a crucial role in
designing various brain-computer interface (BCI) applications. Most of the current …
designing various brain-computer interface (BCI) applications. Most of the current …
Classification of Mental Arithmetic States Using Single Electrode
Mental stress has invariably become a part of every one's life today. According to the
American institute of stress approximately 35% of people are under stress considering 143 …
American institute of stress approximately 35% of people are under stress considering 143 …
Research on motor imaging EEG signals based on VMD
D Liu, B Awudong, X Li, Q Li - Proceedings of the 2024 4th International …, 2024 - dl.acm.org
With the rapid development of brain-computer interface (BCI) technology, it is particularly
important to improve the recognition rate of motor imagery (MI) Electroencephalogram (EEG) …
important to improve the recognition rate of motor imagery (MI) Electroencephalogram (EEG) …
基于全局图振幅排列熵的 EEG 心算分类研究.
王盛淋， 邱祥凯， 王汝清… - … /Shu Ju Cai Ji Yu Chu Li, 2024 - search.ebscohost.com
心算是生活中常使用到的技能, 涉及到多种引起大脑活动变化认知加工环节, 对于心算的脑电(
Electroencephalogram, EEG) 研究有助于提高对认知任务的研究水**. 本文提出了一种全局图 …
Electroencephalogram, EEG) 研究有助于提高对认知任务的研究水**. 本文提出了一种全局图 …
[CITATION][C] Automatic eeg detection of virtual reality motion sickness in resting state based on variational mode decomposition
化成城， 柴立宁， 周占峰， 陈旭， 刘佳 - Journal of Electronic Measurement and …, 2024
[CITATION][C] 基于变分模态分解的休息态虚拟现实晕动症脑电自动检测
化成城， 柴立宁， 周占峰， 陈旭， 刘佳 - 电子测量与仪器学报, 2024