A.I. expert Bin He and his team at Carnegie Mellon University are working on improving noninvasive brain-computer interfaces (BCIs) through the use of innovative…
Browsing: EEG
Researchers have developed a computer-based cognitive task using EEG data to classify the presence and stage of Alzheimer’s disease. The task showed higher accuracy…
This special issue aims to collect papers presenting recent research on brain activity sensing, analysis, and recognition using machine learning techniques on EEG data.…
EEG-based motor imagery (MI) signal classification is a popular area of research due to its applications in robotics, gaming, and medical fields. However, the…
Artificial intelligence (AI) and its subsets, such as machine learning, neural networks, and deep learning, have the potential to revolutionize the medical field. AI…
Brain-computer interfaces (BCI) are used to allow humans to communicate with electronic systems through a connection, typically obtained through electroencephalography (EEG). BCI have essential…
This study examines the interpretability of deep learning (DL) models used in scalp electroencephalography (EEG) based Brain-Computer Interface (BCI) systems. A simulation framework was…
This article discusses the use of digital EEG analysis to detect seizures and other brain conditions from EEG data. It explains the three main…
This article discusses the development of an advanced interpretable deep learning model using multimodal clinical electroencephalogram (EEG) features and demographic information as inputs to…
This article discusses a study that used machine learning (ML) algorithms to predict the existence of brain Aβ+ plaque among SCI or MCI with…