Automated mental arithmetic performance detection using quantum pattern-and triangle pooling techniques with EEG signals
Background Electroencephalography (EEG) signals recorded during mental arithmetic tasks
can be used to quantify mental performance. The classification of these input EEG signals …
can be used to quantify mental performance. The classification of these input EEG signals …
A novel technique for stress detection from EEG signal using hybrid deep learning model
Stress is burgeoning in today's fast-paced lifestyle, and its detection is imperative. An
electroencephalography (EEG) technique is used to identify the brain's activities from the …
electroencephalography (EEG) technique is used to identify the brain's activities from the …
Automated classification of mental arithmetic tasks using recurrent neural network and entropy features obtained from multi-channel EEG signals
The automated classification of cognitive workload tasks based on the analysis of multi-
channel EEG signals is vital for human–computer interface (HCI) applications. In this paper …
channel EEG signals is vital for human–computer interface (HCI) applications. In this paper …
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 …
Subject-Wise Cognitive Load Detection Using Time–Frequency EEG and Bi-LSTM
J Yedukondalu, D Sharma, LD Sharma - Arabian Journal for Science and …, 2024 - Springer
Cognitive load detection using electroencephalogram (EEG) signals is a technique
employed to understand and measure the mental workload or cognitive demands placed on …
employed to understand and measure the mental workload or cognitive demands placed on …
An investigation of the multi-dimensional (1D vs. 2D vs. 3D) analyses of EEG signals using traditional methods and deep learning-based methods
Electroencephalographic (EEG) signals are electrical signals generated in the brain due to
cognitive activities. They are non-invasive and are widely used to assess neurodegenerative …
cognitive activities. They are non-invasive and are widely used to assess neurodegenerative …
Mental performance classification using fused multilevel feature generation with EEG signals
Mental performance classification is a critical issue for brain-computer interfaces. Accurate
and reliable classification of good or bad mental performance gives important clues for the …
and reliable classification of good or bad mental performance gives important clues for the …
[HTML][HTML] BCI-AMSH: A MATLAB based open-source brain computer interface assistive application for mental stress healing
CR Rashmi, CP Shantala - e-Prime-Advances in Electrical Engineering …, 2023 - Elsevier
Numerous Brain computer interface (BCI) assistive software applications or toolboxes help
to monitor the status of brain through Electroencephalogram (EEG); however, currently there …
to monitor the status of brain through Electroencephalogram (EEG); however, currently there …
Classification of electroencephalograms during mathematical calculations using deep learning
U Goenka, P Patil, K Gosalia… - 2022 IEEE 23rd …, 2022 - ieeexplore.ieee.org
Classifying Electroencephalogram (EEG) signals helps in understanding Brain-Computer
Interface (BCI). EEG signals are vital in studying how the human mind functions. In this …
Interface (BCI). EEG signals are vital in studying how the human mind functions. In this …
Evaluation of EEG Signals by Spectral Peak Methods and Statistical Correlation for Mental State Discrimination Induced by Arithmetic Tasks
Bringing out brain activity through the interpretation of EEG signals is a challenging problem
that involves combined methods of signal analysis. The issue of classifying mental states …
that involves combined methods of signal analysis. The issue of classifying mental states …