Support vector machines to detect physiological patterns for EEG and EMG-based human–computer interaction: a review
Support vector machines (SVMs) are widely used classifiers for detecting physiological
patterns in human–computer interaction (HCI). Their success is due to their versatility …
patterns in human–computer interaction (HCI). Their success is due to their versatility …
A review of rapid serial visual presentation-based brain–computer interfaces
S Lees, N Dayan, H Cecotti, P McCullagh… - Journal of neural …, 2018 - iopscience.iop.org
Rapid serial visual presentation (RSVP) combined with the detection of event-related brain
responses facilitates the selection of relevant information contained in a stream of images …
responses facilitates the selection of relevant information contained in a stream of images …
Single-source to single-target cross-subject motor imagery classification based on multisubdomain adaptation network
In the electroencephalography (EEG) based cross-subject motor imagery (MI) classification
task, the device and subject problems can cause the time-related data distribution shift …
task, the device and subject problems can cause the time-related data distribution shift …
The effects of day-to-day variability of physiological data on operator functional state classification
JC Christensen, JR Estepp, GF Wilson, CA Russell - NeuroImage, 2012 - Elsevier
The application of pattern classification techniques to physiological data has undergone
rapid expansion. Tasks as varied as the diagnosis of disease from magnetic resonance …
rapid expansion. Tasks as varied as the diagnosis of disease from magnetic resonance …
Motor imagery classification using inter-task transfer learning via a channel-wise variational autoencoder-based convolutional neural network
Highly sophisticated control based on a brain-computer interface (BCI) requires decoding
kinematic information from brain signals. The forearm is a region of the upper limb that is …
kinematic information from brain signals. The forearm is a region of the upper limb that is …
Single-trial classification of event-related potentials in rapid serial visual presentation tasks using supervised spatial filtering
H Cecotti, MP Eckstein… - IEEE transactions on …, 2014 - ieeexplore.ieee.org
Accurate detection of single-trial event-related potentials (ERPs) in the
electroencephalogram (EEG) is a difficult problem that requires efficient signal processing …
electroencephalogram (EEG) is a difficult problem that requires efficient signal processing …
A subject transfer framework for EEG classification
This paper proposes a subject transfer framework for EEG classification. It aims to improve
the classification performance when the training set of the target subject (namely user) is …
the classification performance when the training set of the target subject (namely user) is …
Single-trial EEG classification using spatio-temporal weighting and correlation analysis for RSVP-based collaborative brain computer interface
Objective: Since single brain computer interface (BCI) is limited in performance, it is
necessary to develop collaborative BCI (cBCI) systems which integrate multi-user …
necessary to develop collaborative BCI (cBCI) systems which integrate multi-user …
[HTML][HTML] How do human detect targets of remote sensing images with visual attention?
Human visual attention is the basis of target recognition, change detection and classification
in remote sensing images. However, the human visual attention of remote sensing images …
in remote sensing images. However, the human visual attention of remote sensing images …
Operator functional state classification using least-square support vector machine based recursive feature elimination technique
Z Yin, J Zhang - Computer methods and programs in biomedicine, 2014 - Elsevier
This paper proposed two psychophysiological-data-driven classification frameworks for
operator functional states (OFS) assessment in safety-critical human-machine systems with …
operator functional states (OFS) assessment in safety-critical human-machine systems with …