A review on the computational methods for emotional state estimation from the human EEG
A growing number of affective computing researches recently developed a computer system
that can recognize an emotional state of the human user to establish affective human …
that can recognize an emotional state of the human user to establish affective human …
An application of the Kalman filter for EEG/ERP signal enhancement with the autoregressive realisation
Abstract Electroencephalogram/Event-related-potentials (EEG/ERP) signals have lower
amplitude, are popularly known for their nonstationary nature and are easily exposed to …
amplitude, are popularly known for their nonstationary nature and are easily exposed to …
EEG/ERP adaptive noise canceller design with controlled search space (CSS) approach in cuckoo and other optimization algorithms
This paper explores the migration of adaptive filtering with swarm intelligence/evolutionary
techniques employed in the field of electroencephalogram/event-related potential noise …
techniques employed in the field of electroencephalogram/event-related potential noise …
Detection of human emotions using features based on the multiwavelet transform of EEG signals
V Bajaj, RB Pachori - Brain-Computer Interfaces: Current Trends and …, 2015 - Springer
Emotion classification based on electroencephalogram (EEG) signals is a relatively new
area of research in the development of brain computer interface (BCI) system with …
area of research in the development of brain computer interface (BCI) system with …
Adaptive filtering of EEG/ERP through noise cancellers using an improved PSO algorithm
In this paper, event related potential (ERP) generated due to hand movement is detected
through the adaptive noise canceller (ANC) from the electroencephalogram (EEG) signals …
through the adaptive noise canceller (ANC) from the electroencephalogram (EEG) signals …
Classifier-based latency estimation: a novel way to estimate and predict BCI accuracy
DE Thompson, S Warschausky… - Journal of neural …, 2012 - iopscience.iop.org
Objective. Brain–computer interfaces (BCIs) that detect event-related potentials (ERPs) rely
on classification schemes that are vulnerable to latency jitter, a phenomenon known to occur …
on classification schemes that are vulnerable to latency jitter, a phenomenon known to occur …
Tensor factorization approach for ERP-based assessment of schizotypy in a novel auditory oddball task on perceived family stress
Objective. Schizotypy, a potential phenotype for schizophrenia, is a personality trait that
depicts psychosis-like signs in the normal range of psychosis continuum. Family …
depicts psychosis-like signs in the normal range of psychosis continuum. Family …
Bayesian estimation of ERP components from multicondition and multichannel EEG
Extraction and separation of functionally different event-related potentials (ERPs) from
electroencephalography (EEG) is a long-standing problem in cognitive neuroscience. In this …
electroencephalography (EEG) is a long-standing problem in cognitive neuroscience. In this …
Single-trial event-related potential extraction through one-unit ICA-with-reference
Objective. In recent years, ICA has been one of the more popular methods for extracting
event-related potential (ERP) at the single-trial level. It is a blind source separation …
event-related potential (ERP) at the single-trial level. It is a blind source separation …
Low-rank Tensor Restoration for ERP extraction
ZS Bonab, MB Shamsollahi - Biomedical Signal Processing and Control, 2024 - Elsevier
Event-related potential (ERP) data is essentially multi-dimensional, with correlated data in
some spaces. Therefore, matrix and vector analysis results in structural information loss …
some spaces. Therefore, matrix and vector analysis results in structural information loss …