Brain–machine interfaces (BMIs) create closed-loop control systems that interact with the
brain by recording and modulating neural activity and aim to restore lost function, most …

Background A substantial number of clinical studies have demonstrated the functional
recovery induced by the use of brain-computer interface (BCI) technology in patients after …

Brain-computer interface (BCI) technologies aim to provide a bridge between the human
brain and external devices. Prior research using non-invasive BCI to control virtual objects …

Mental-tasks based brain–computer interfaces (MT-BCIs) allow their users to interact with an
external device solely by using brain signals produced through mental tasks. While MT-BCIs …

Neurofeedback (NFB) is emerging as a promising technique that enables self-regulation of
ongoing brain oscillations. However, despite a rise in empirical evidence attesting to its …

Neuroplasticity may play a critical role in developing robust, naturally controlled
neuroprostheses. This learning, however, is sensitive to system changes such as the neural …

This work aims at corroborating the importance and efficacy of mutual learning in motor
imagery (MI) brain–computer interface (BCI) by leveraging the insights obtained through our …

Brain-machine interfaces (BMIs) aim to help people with paralysis by decoding movement-
related neural signals into control signals for guiding computer cursors, prosthetic arms, and …

The last decade has seen a flowering of applications driven by brain–machine interfaces
(BMIs), particularly brain-actuated robotic devices designed to restore the independence of …

Mind-controlled wheelchairs are an intriguing assistive mobility solution applicable in
complete paralysis. Despite progress in brain-machine interface (BMI) technology, its …