A review on transfer learning in EEG signal analysis
Electroencephalogram (EEG) signal analysis, which is widely used for human-computer
interaction and neurological disease diagnosis, requires a large amount of labeled data for …
interaction and neurological disease diagnosis, requires a large amount of labeled data for …
A comprehensive review on critical issues and possible solutions of motor imagery based electroencephalography brain-computer interface
Motor imagery (MI) based brain–computer interface (BCI) aims to provide a means of
communication through the utilization of neural activity generated due to kinesthetic …
communication through the utilization of neural activity generated due to kinesthetic …
Locally robust EEG feature selection for individual-independent emotion recognition
Z Yin, L Liu, J Chen, B Zhao, Y Wang - Expert Systems with Applications, 2020 - Elsevier
Brain computer interface (BCI) systems can decode brain affective activities into
interpretable features and facilitate emotional human–computer interaction. However …
interpretable features and facilitate emotional human–computer interaction. However …
Beyond supervised learning for pervasive healthcare
The integration of machine/deep learning and sensing technologies is transforming
healthcare and medical practice. However, inherent limitations in healthcare data, namely …
healthcare and medical practice. However, inherent limitations in healthcare data, namely …
A comprehensive review of endogenous EEG-based BCIs for dynamic device control
Electroencephalogram (EEG)-based brain–computer interfaces (BCIs) provide a novel
approach for controlling external devices. BCI technologies can be important enabling …
approach for controlling external devices. BCI technologies can be important enabling …
EEG-based BCIs on motor imagery paradigm using wearable technologies: a systematic review
In recent decades, the automatic recognition and interpretation of brain waves acquired by
electroencephalographic (EEG) technologies have undergone remarkable growth, leading …
electroencephalographic (EEG) technologies have undergone remarkable growth, leading …
Deep learning based inter-subject continuous decoding of motor imagery for practical brain-computer interfaces
Inter-subject transfer learning is a long-standing problem in brain-computer interfaces (BCIs)
and has not yet been fully realized due to high inter-subject variability in the brain signals …
and has not yet been fully realized due to high inter-subject variability in the brain signals …
An EEG-EMG correlation-based brain-computer interface for hand orthosis supported neuro-rehabilitation
Background Corticomuscular coupling has been investigated for long, to find out the
underlying mechanisms behind cortical drives to produce different motor tasks. Although …
underlying mechanisms behind cortical drives to produce different motor tasks. Although …
Optimization of preprocessing stage in EEG based BCI systems in terms of accuracy and timing cost
E Dagdevir, M Tokmakci - Biomedical Signal Processing and Control, 2021 - Elsevier
Performance of the motor imagery-based brain computer interface (MI-BCI) systems has
been tried to improve by the researchers with novel approaches and methods used on …
been tried to improve by the researchers with novel approaches and methods used on …
BCIAUT-P300: A multi-session and multi-subject benchmark dataset on autism for P300-based brain-computer-interfaces
There is a lack of multi-session P300 datasets for Brain-Computer Interfaces (BCI). Publicly
available datasets are usually limited by small number of participants with few BCI sessions …
available datasets are usually limited by small number of participants with few BCI sessions …