Paired Associative Stimulation with Brain-Computer Interfaces: A New Paradigm for Stroke Rehabilitation

In conventional rehabilitation therapy to help persons with stroke recover movement, there is no objective way to evaluate each patient's motor imagery. Thus, patients may receive rewarding feedback even when they are not complying with the task instructions to imagine specific movements. Paired associative stimulation PAS uses brain-computer interface BCI technology to evaluate movement imagery in real-time, and use this information to control feedback presented to the patient. We introduce this approach and the RecoveriX system, a hardware and software platform for PAS. We then present initial results from two stroke patients who used RecoveriX, followed by future directions.

[1]  S. Silvoni,et al.  Brain-Computer Interface in Stroke: A Review of Progress , 2011, Clinical EEG and neuroscience.

[2]  M. Molinari,et al.  Brain Computer Interface for Hand Motor Function Restoration and Rehabilitation , 2012 .

[3]  Brendan Z. Allison,et al.  The Hybrid BCI , 2010, Frontiers in Neuroscience.

[4]  José del R. Millán,et al.  Recent and Upcoming BCI progress: Overview, Analysis, and Recommendations , 2012 .

[5]  Cuntai Guan,et al.  Brain-computer interface-based robotic end effector system for wrist and hand rehabilitation: results of a three-armed randomized controlled trial for chronic stroke , 2014, Front. Neuroeng..

[6]  M. Molinari,et al.  Rehabilitation of gait after stroke: a review towards a top-down approach , 2011, Journal of NeuroEngineering and Rehabilitation.

[7]  Rupert Ortner,et al.  Human-Computer Confluence for Rehabilitation Purposes after Stroke , 2013, HCI.

[8]  Rupert Ortner,et al.  A Motor Imagery Based Brain-Computer Interface for Stroke Rehabilitation , 2012, Annual Review of Cybertherapy and Telemedicine.

[9]  G. Pfurtscheller,et al.  Designing optimal spatial filters for single-trial EEG classification in a movement task , 1999, Clinical Neurophysiology.

[10]  G. Pfurtscheller,et al.  How many people are able to operate an EEG-based brain-computer interface (BCI)? , 2003, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[11]  José Luis Pons Rovira,et al.  A Closed-Loop Brain–Computer Interface Triggering an Active Ankle–Foot Orthosis for Inducing Cortical Neural Plasticity , 2014, IEEE Transactions on Biomedical Engineering.

[12]  José del R. Millán,et al.  BNCI Horizon 2020: Towards a Roadmap for the BCI Community , 2015 .

[13]  G. Pfurtscheller,et al.  Imagery of motor actions: differential effects of kinesthetic and visual-motor mode of imagery in single-trial EEG. , 2005, Brain research. Cognitive brain research.