NeurAugVR

Abstract

Every year millions of people worldwide suffer from stroke, being one of the leading causes of death and longterm disability. This leads to cognitive and motor impairments, resulting in loss of independence in their daily life together with an additional psychological impact in mood disorders and depression. Evolving to a chronic condition, stroke requires continuous rehabilitation and therapy. Personalised Virtual-Reality (VR) approaches have been shown to accelerate the recovery process compared to non-Information and communication technologies (ICT) based interventions. However, most of these novel VR approaches are suitable only for a reduced subset of patients, generally those with better recovery prognostics and better motor control. Thus, the idea of training the central nervous system was established, through EEG-based neurofeedback (NF) and motor-imagery (MI). Although the benefits of MI-NF have been illustrated in a plethora of studies, the reduced ability for stroke patients to use NF does not allow an accurate control, reducing the capabilities of MI-NF systems.

The aim of this project is to develop a novel and more inclusive rehabilitation system with the use of novel ICT technologies, in order to overcome current limitations. This will be achieved by identifying the neural correlates of motor action during motor imagery through brain imaging (fMRI), and differences in brain activation with different training feedback protocols for formulating user-specific models that will be used later in NF-MI rehabilitation sessions. This will facilitate the use of neural interfaces to train the central nervous system; specifically, we will develop a personalized EEG-based immersive NF through VR for MI training. The ultimate goal is to generalize the findings into a VR-NF-MI training paradigm for both admitted and ambulatory patients as well as continued domestic care.

The impact of the project can be expected on multiple levels. At the scientific level, it will contribute to further understanding the neuro-physiological brain plasticity mechanisms underlying motor recovery after a stroke; and provide yet necessary further evidence on the benefits of ICT driven rehabilitation approaches

On the technological level, it proposes novel methodologies for training and monitoring rehabilitation after a brain lesion; offering to the community an open architecture to share and facilitate the development of future ICT systems for rehabilitation. Further, given the nature of this research area the potential socio-economic impact of such a system is significant, allowing for novel personalized and home-based eHealth solutions for patients. Thus, also decreasing the financial burden in the national health system.

Finally, the real-world deployment of this unique system with our clinical partners will provide us extremely valuable data, which will help us to validate and quantify the impact of such novel approach.

Aim of the project

The aim of this project is to develop a novel and more inclusive motor rehabilitation paradigm with the use of novel ICT technologies, that overcomes current limitations, especially for stroke patients with low level of motor control.

Our approach combines the latest research findings for effective stroke rehabilitation together with novel biomedical systems for brain monitoring (EEG, fMRI) and VR biofeedback.

This will be achieved following 3 main research objectives:

1. To understand the brain activity during MI-NF training using simultaneous EEG-fMRI acquisition. This will be achieved by developing computational models for inferring EEG features from fMRI motor activation patterns measured during the execution of training, thus exploiting the higher spatial resolution of fMRI. These individualized computational models will be exploited in a subsequent EEG-based VR-MI-NF training.
2. Clinical evaluation of the impact of the novel upper-limb NF paradigm to train motor function through inclusive rehabilitation with the use of BCIs for neurofeedback on a longitudinal intervention.
3. To quantify the extent of motor recovery and cortical reorganization induced by the NF-VR paradigm by comparing a pre, post and follow up assessments.

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• Vourvopoulos, A., Jorge, C., Abreu, R., Figueiredo, P., Fernandes, J.-C., & Bermúdez i Badia, S. (2019). Efficacy and Brain Imaging Correlates of an Immersive Motor Imagery BCI-driven VR System for Upper Limb Motor Rehabilitation: A Clinical Case Report. Front. Hum. Neurosci. (https://doi.org/10.3389/fnhum.2019.00244)

SESARAM

NeuroRehabLab / ARDITI

LaSEEB