RehabNetProject reference: 303891
Funded under :
REHABNET: NEUROSCIENCE BASED INTERACTIVE SYSTEMS FOR MOTOR REHABILITATION
Total cost:EUR 100 000
EU contribution:EUR 100 000
Call for proposal:FP7-PEOPLE-2011-CIGSee other projects for this call
Funding scheme:MC-CIG - Support for training and career development of researcher (CIG)
Given the aging of the population, stroke will become one of the main contributors to the burden of disease by 2030, being one of the major challenges for modern societies and healthcare systems. Many stroke survivors depend on their relatives and require continuous rehabilitation and therapy, which represents a significant psychosocial and economical burden for patients, relatives and healthcare systems. Public healthcare can not always provide patients with the rehabilitation duration and frequency they may need. Thus, there is a pressing need to find more effective solutions.
Recently, the more mature status of novel technologies and new neuroscientific findings have allowed the rapid growth of computed mediated rehabilitation tools for stroke. Unfortunately, most of this rehabilitation approaches require patients to have a high degree of motor control in order to use them. Thus, the more impaired patients - and therefore those in more need of more effective and alternative treatments - can not benefit from these approaches. Based on the current knowledge on the brain mechanisms for recovery, RehabNet will develop, evaluate and deploy a novel ICT platform for personalized and interactive computer-based rehabilitation for stroke patients with upper limb motor deficits. The goal of RehabNet is to develop effective neuroscience based motor training paradigms for the rehabilitation of the upper limbs that are accessible to all patients, particularly those with the worst prognostic. Hence, Rehabnet will develop a novel robotic assisted Virtual Reality (VR) training system that is able to restore active movement in low mobility patients, and that collecs synchronized real-time behavioral, performance and brain activity data. On a second stage, RehabNet will use these unique dataset to propose and evaluate a novel rehabilitation paradigm using mental practice by means of a VR neurofeedback system for the clinical and at home rehabilitation of no mobility patients.
EU contribution: EUR 100 000
CAMINHO DA PENTEADA POLO CIENTIFICO E TECNOLOGICO DA MADEIRA
9020 105 FUNCHAL MADEIRA
Tel.: +351 291 72 1209