Brain-Computer Interface in Stroke: A Review of Progress

Abstract

Brain-computer interface (BCI) technology has been used for rehabilitation after stroke and there are a number of reports involving stroke patients in BCI-feedback training. Most publications have demonstrated the efficacy of BCI technology in post-stroke rehabilitation using output devices such as Functional Electrical Stimulation, robot, and orthosis. The aim of this review is to focus on the progress of BCI-based rehabilitation strategies and to underline future challenges. A brief history of clinical BCI-approaches is presented focusing on stroke motor rehabilitation. A context for three approaches of a BCI-based motor rehabilitation program is outlined: the substitutive strategy, classical conditioning and operant conditioning. Furthermore, we include an overview of a pilot study concerning a new neuro-forcefeedback strategy. This pilot study involved healthy participants. Finally we address some challenges for future BCI-based rehabilitation.

Efficient neuroplasticity induction in chronic stroke patients by an associative brain-computer interface

“…Taken together, the results from the BCI associative and the BCI nonassociative interventions underline the importance of the correct sequence of signals for inducing long-lasting plastic changes. The critical importance of the delay between motor command and sensory input shown here for patients and in previous studies for healthy subjects (Mrachacz-Kersting et al 2012a) may also explain the substantially less efficient outcome of BCI neuromodulation in stroke patients in previous studies (for review see Silvoni et al 2011).…”

Subject-specific time-frequency selection for multi-class motor imagery-based BCIs using few Laplacian EEG channels

“…Motor imagery (MI)-based BCI is one typical EEG-based BCI, which predicts the subject's motor intentions through classifying sensorimotor rhythms. Several factors indicate that MI-based BCI is quite promising for motor rehabilitation [11] and general public applications. On the one hand, this type of BCI employs the signals from the sensorimotor cortex, which are directly linked to the motor output pathway in the brain.…”

Using a motor imagery questionnaire to estimate the performance of a Brain–Computer Interface based on object oriented motor imagery

“…Injuries to the CNS may influence execution of both covert and overt movements , Maulouin and Richards 2010, Butler and Page 2006 that are accompanied with changes in the ERS/ERD response [Pfurtscheller et al 1980, Enzinger et al 2008, Silvoni et al 2011.…”