. Mind-wandering is a mental phenomenon where the internal thought process disengages from the external environment periodically. In the current study, we trained EEG classifiers using convolutional neural networks (CNNs) to track mind-wandering acro...
Confusion is the primary epistemic emotion in the learning process, influencing students' engagement and whether they become frustrated or bored. However, research on confusion in learning is still in its early stages, and there is a need to better u...
. Automated artefact detection in the neonatal electroencephalogram (EEG) is crucial for reliable automated EEG analysis, but limited availability of expert artefact annotations challenges the development of deep learning models for artefact detectio...
. This study aims to design and implement the first deep learning (DL) model to classify subjects in the prodromic states of Alzheimer's disease (AD) based on resting-state electroencephalographic (EEG) signals.. EEG recordings of 17 healthy controls...
Robot-assisted rehabilitation training is an effective way to assist rehabilitation therapy. So far, various robotic devices have been developed for automatic training of central nervous system following injury. Multimodal stimulation such as visual ...
High-density electromyography (HD-EMG) decomposition algorithms are used to identify individual motor unit (MU) spike trains, which collectively constitute the neural code of movements, to predict motor intent. This approach has advanced from offline...
Intracranially-recorded interictal high-frequency oscillations (HFOs) have been proposed as a promising spatial biomarker of the epileptogenic zone. However, HFOs can also be recorded in the healthy brain regions, which complicates the interpretation...
. The limited functionality of hand prostheses remains one of the main reasons behind the lack of its wide adoption by amputees. Indeed, while commercial prostheses can perform a reasonable number of grasps, they are often inadequate for manipulating...
Automated interictal epileptiform discharge (IED) detection has been widely studied, with machine learning methods at the forefront in recent years. As computational resources become more accessible, researchers have applied deep learning (DL) to IED...
. Auditory attention decoding (AAD) determines which speaker the listener is focusing on by analyzing his/her EEG. Convolutional neural network (CNN) was adopted to extract spectro-spatial-feature (SSF) from short-time-interval of EEG to detect audit...