Transactions on Neural Systems and Rehabilitation Engineering

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Age-Related Changes in Vibro-Tactile EEG Response and Its Implications in BCI Applications: A Comparison Between Older and Younger Populations
    The rapid increase in the number of older adults around the world is accelerating research in applications to support age-related conditions, such as brain–computer interface (BCI) applications for post-stroke neurorehabilitation. The signal processing algorithms for electroencephalogram (EEG) and other physiological... Read more
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Ear-EEG-Based Objective Hearing Threshold Estimation Evaluated on Normal Hearing Subjects
Integration of auditory evoked potential techniques in hearing aids potentially enable assessment of the users hearing on a regular basis. Hearing threshold levels can be estimated in the clinic using the objective EEG-based technique of auditory steady state response (ASSR).... Read more
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A Benchmark Dataset for SSVEP-Based Brain-Computer Interfaces
    This paper presents a benchmark steady-state visual evoked potential (SSVEP) dataset acquired with a 40-target brain-computer interface (BCI) speller. The dataset consists of 64-channel Electroencephalogram (EEG) data from 35 healthy subjects (8 experienced and 27 naïve) while they performed a... Read more
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Imagined Hand Clenching Force and Speed Modulate Brain Activity and Are Classified by NIRS Combined With EEG
      Simultaneous acquisition of brain activity signals from the sensorimotor area using NIRS combined with EEG, imagined hand clenching force and speed modulation of brain activity, as well as 6-class classification of these imagined motor parameters by NIRS-EEG were explored. Near... Read more
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Discriminative Manifold Learning Based Detection of Movement-Related Cortical Potentials
The detection of voluntary motor intention from EEG has been applied to closed-loop brain–computer interfacing (BCI). The movement-related cortical potential (MRCP) is a low frequency component of the EEG signal, which represents movement intention, preparation, and execution. In this study,... Read more
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Evaluate the feasibility of using frontal SSVEP to implement an SSVEP – based BCI in Young, Elderly and ALS groups
This paper studied the amplitude-frequency characteristic of frontal steady-state visual evoked potential (SSVEP) and its feasibility as a control signal for brain computer interface (BCI). SSVEPs induced by different stimulation frequencies, from 13 ~ 31 Hz in 2 Hz steps,... Read more
Articles, Published Articles
Comparative Study of Wavelet Based Unsupervised Ocular Artifact Removal Techniques for Single Channel EEG Data
Electroencephalogram (EEG) is a technique for recording asynchronous activation of neuronal firing inside the brain with non-invasive scalp electrodes. Artifacts such as eye blink activities can corrupt these neuronal signals. While ocular artifact (OA) removal is well investigated for multiple... Read more
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FORCe: Fully Online and Automated Artifact Removal for Brain-Computer Interfacing
A fully automated and online artifact removal method for the electroencephalogram (EEG) is developed for use in braincomputer interfacing (BCI). The method (FORCe) is based upon a novel combination of wavelet decomposition, independent component analysis, and thresholding. FORCe is able... Read more
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Sliding HDCA: Single-Trial EEG Classification to Overcome and Quantify Temporal Variability
A. Marathe, A. Ries, and K. McDowell ACCESS PAPER DATA READ FULL ARTICLE ON IEEE XPLORE Abstract Patterns of neural data obtained from electroencephalography (EEG) can be classified by machine learning techniques to increase human-system performance. In controlled laboratory settings this classification approach works well; however, transitioning these... Read more
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L1-Regularized Multiway Canonical Correlation Analysis for SSVEP-Based BCI
Y. Zhang, G. Zhou, J. Jin, M. Wang, X. Wang, and A. Cichocki   ACCESS PAPER DATA READ FULL ARTICLE ON IEEE XPLORE Abstract Canonical correlation analysis (CCA) between recorded electroencephalogram (EEG) and designed reference signals of sine-cosine waves usually works well for steady-state visual evoked potential (SSVEP) recognition... Read more