Brain–computer interfaces have revolutionized the field of neuroscience by providing a
solution for paralyzed patients to control external devices and improve the quality of daily …

Falls are an important factor in significantly deteriorating quality of life of older adults,
consequently leading to both physical and psychological harm. A wearable-based fall …

Animals of the same species exhibit similar behaviours that are advantageously adapted to
their body and environment. These behaviours are shaped at the species level by selection …

Muscle electrophysiology has emerged as a powerful tool to drive human machine
interfaces, with many new recent applications outside the traditional clinical domains, such …

Neuromechanical studies investigate how the nervous system interacts with the
musculoskeletal (MSK) system to generate volitional movements. Such studies have been …

Brain–computer interface (BCI) has been developed for decades to directly establish
communication between human brain and external devices. Current BCI has been widely …

Emotion recognition based on EEG signals has been a challenging task. The acquisition of
EEG signals is complex, time-consuming, and has a high overhead. Artificial Intelligence …

Objective. Deep learning is increasingly used for brain–computer interfaces (BCIs).
However, the quantity of available data is sparse, especially for invasive BCIs. Data …

In order to achieve more sensitive mental fatigue assessment (MFA) based on an arbitrary
channel EEG, this study proposed a series of feature extraction methods that combine …

Practical brain–computer interfaces should be able to decipher brain signals and
dynamically adapt to brain fluctuations. This, however, requires a decoder capable of …