Electroencephalogram (EEG)-based brain–computer interfaces (BCIs) provide a novel
approach for controlling external devices. BCI technologies can be important enabling …

In recent decades, the automatic recognition and interpretation of brain waves acquired by
electroencephalographic (EEG) technologies have undergone remarkable growth, leading …

The effects of corticomuscular connectivity during object manipulation tasks with different
haptic sensations have not been quantitatively investigated. Connectivity analyses enable …

Abstract Current Motor Imagery Brain-Computer Interfaces (MI-BCI) require a lengthy and
monotonous training procedure to train both the system and the user. Considering many …

Social isolation is likely to be one of the most serious health outcomes for the elderly due to
the COVID-19 pandemic, especially for seniors living alone at home. In fact, two approaches …

The brain has been understood as an interconnected neural network generally modeled as
a graph to outline the functional topology and dynamics of brain processes. Classic graph …

As the main component of Brain-computer interface (BCI) technology, the classification
algorithm based on EEG has developed rapidly. The previous algorithms were often based …

When individuals listen to speech, their neural activity phase-locks to the slow temporal
rhythm, which is commonly referred to as “neural tracking”. The neural tracking mechanism …

Stroke is a neurological syndrome that usually causes a loss of voluntary control of
lower/upper body movements, making it difficult for affected individuals to perform Activities …

Acquiring biopotentials with fidelity using low-cost circuits is a significant challenge in
biomedical instrumentation. In this perspective, our goal is to investigate the characteristics …