A brain-machine interface (BMI) is about transforming neural activity into action and sensation into perception (Figure 1). In a BMI system, neural signals recorded from the brain are fed into a decoding algorithm that translates these signals into motor o ...
Brain-machine interfaces (BMI) usually decode movement parameters from cortical activity to control neuroprostheses. This requires subjects to learn to modulate their brain activity to convey all necessary information, thus imposing natural limits on the c ...
Human brain is organized by a large number of functionally correlated but spatially distributed cortical neurons. Cognitive processes are usually associated with dynamic interactions among multiple brain regions. Therefore, the understanding of brain funct ...
Successful operation of motor imagery (MI)-based brain-computer interfaces (BCI) requires mutual adaptation between the human subject and the BCI. Traditional training methods, as well as more recent ones based on co-adaptation, have mainly focused on the ...
In this paper, the results of a pilot interview study with 19 subjects participating in an EEG-based non-invasive brain–computer interface (BCI) research study on stroke rehabilitation and assistive technology and of a survey among 17 BCI professionals are ...
