@article{8897,

title = {Using a hybrid brain computer interface and virtual reality system to monitor and promote cortical reorganization through motor activity and motor imagery training},

author = {Sergi Bermúdez Badia and A. b García Morgade and H. Samaha and P. F. M. J. Verschure},

url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-84874980376&partnerID=40&md5=17fa0fd00472b9e6df6b643f349d04da},

year  = {2013},

date = {2013-01-01},

urldate = {2013-01-01},

journal = {IEEE Transactions on Neural Systems and Rehabilitation Engineering [Impact Factor (JCR SCI 2012): 0.907]},

volume = {21},

number = {2},

pages = {174-181},

abstract = {<p>Stroke is one of the leading causes of adult disability with high economical and societal costs. In recent years, novel rehabilitation paradigms have been proposed to address the life-long plasticity of the brain to regain motor function. We propose a hybrid brain-computer interface (BCI) - virtual reality (VR) system that combines a personalized motor training in a VR environment, exploiting brain mechanisms for action execution and observation, and a neuro-feedback paradigm using mental imagery as a way to engage secondary or indirect pathways to access undamaged cortico-spinal tracts. Furthermore, we present the development and validation experiments of the proposed system. More specifically, EEG data on nine naïve healthy subjects show that a simultaneous motor activity and motor imagery paradigm is more effective at engaging cortical motor areas and related networks to a larger extent. Additionally, we propose a motor imagery driven BCI-VR version of our system that was evaluated with nine different healthy subjects. Data show that users are capable of controlling a virtual avatar in a motor imagery training task that dynamically adjusts its difficulty to the capabilities of the user. User self-report questionnaires indicate enjoyment and acceptance of the proposed system. © 2001-2011 IEEE.</p>},

note = {<p>cited By (since 1996)1</p>},

keywords = {},

pubstate = {published},

tppubtype = {article}

}