The primary focus of this article was to review the current understanding of motor imagery (MI) as a cognitive process and thereby explore correlated biosignals for devising advanced brain-computer interfaces (BCIs) helping toward overcoming the limitations of current systems.
To this end, the article first outlines the process of performing MI, ensuring kinesthetic experiences, and explores the literature to ascertain main brain areas that are activated during MI. Mental chronometry as a conventional method of assessing MI is then discussed, and its main limitation of not being able to measure MI vividness is highlighted. Neurophysiology and neuroelectrophysiology of MI are then analyzed to explain the phenomena of event-related desynchronization and event-related synchronization occurring in the sensorimotor rhythms, used as the principal feature in electroencephalogram-based BCIs.
The current understanding on the effect of MI on regional cerebral blood flow and neural metabolism is then reviewed with the objective of explaining how functional magnetic resonance imaging and near infrared spectroscopy can be used to devise a metabolic BCI system.
The literature is then reviewed to explore the current understanding on the effect of MI on peripheral nervous system causing variations in autonomic responses. Most importantly, the review identifies a range of biosignals including oxygen consumption, respiratory rate, heart rate, and skin resistance, which have strong potential for developing enhanced BCI devices either alone or in combination with other signals including electroencephalogram and near-infrared spectroscopy, through multisensor integration.
The primary focus of this paper is to review the current understanding of motor imagery as a cognitive process and thereby explore correlated bio-signals for devising advanced brain-computer interfaces helping to overcome the limitations of the current system.
Corresponding author: Rakesh Kumar Sinha, PhD, is associate professor at the Center for Biomedical Instrumentation in the Department of Electrical and Electronics Engineering of the Birla Institute of Technology in Mesra, Ranchi, Jharkhand, India. He can be reached at email@example.com or 91-9431382724.
Girijesh Prasad is professor at the Intelligent Systems Research Centre of the University of Ulster, Magee Campus, Londonderry, Northern Ireland, United Kingdom. Girijesh Prasad can be reached at firstname.lastname@example.org.
The authors declares no conflicts of interest.