Objective: Concealable, miniaturized electroencephalography (mini-EEG) recording devices
are crucial enablers toward long-term ambulatory EEG monitoring. However, the resulting …

Channel selection or electrode placement for neural decoding is a commonly encountered
problem in electroencephalography (EEG). Since evaluating all possible channel …

Recent technological advances in the design of concealable miniature electroencephalography
(mini-EEG) devices are paving the way towards 24/7 neuromonitoring applications in …

Objective. Unobtrusive electroencephalography (EEG) monitoring in everyday life requires
the availability of highly miniaturized EEG devices (mini-EEGs), which ideally consist of a …

In sensor arrays or sensor networks, tracking each sensors utility helps in excluding those
which do not sufficiently contribute to the task at hand, thereby reducing energy consumption …

Feature selection techniques are very useful approaches for dimensionality reduction in
data analysis. They provide interpretable results by reducing the dimensions of the data to a …

The ability to record brain signals during daily life activities would allow to deepen our
understanding of the human brain, its related pathologies (such as epilepsy and Alzheimer’s dis-…

Many applications of data science require the study of highly multi-dimensional data. A high
number of 37 dimensions implies a high computational cost as well as a large amount of …

Electroencephalography (EEG) is a widely used modality for monitoring neural activity and
is currently viewed as one of the most promising non-invasive techniques for future chronic …

Electroencephalography (EEG) is an essential tool in clinical practice for the diagnosis and
monitoring of people with epilepsy. Manual annotation of epileptic seizures is a time …