Research team
Expertise
*Clinical stroke research focusing on prehospital diagnostics (telemedicine), wearables (HRV measurement) and predictors of outcome (gait analysis, DTI imaging techniques). *Participation in international databases and consortia (BEL-FMD, NOAC-ISP, SiFAP) *Prinical investigator / national coordinator for industry-led RCT's (eg. THALES, NAVIGATE-ESUS, ETNA-AF, RESTORE BRAIN, AXIOMATIC-SSP trial).
Unravelling the relationship between brain structural connectivity and gait outcome in stroke survivors: a deeper look into longitudinal gait recovery.
Abstract
Stroke incidence is increasing and, consequently, so are the number of motor impaired survivors. Whereas patient tailored rehabilitation strategies are believed to greatly improve recovery, a reliable biomarker for gait outcome prediction that enables such patient tailored rehabilitation is currently missing. Therefore, this project aims to explore whether brain structural connectivity between areas responsible for gait can be used as a biomarker for gait recovery prediction. This will be done by characterizing brain connectivity during the first 6 months after stroke using diffusion magnetic resonance imaging (dMRI) and correlating these findings with gait recovery as measured by a comprehensive gait analysis. Brain connectivity will be assessed considering 12 brain areas and 18 white matter pathways between them. Gait analysis will include data on kinetics, kinematics and muscle activity. All results will be used for a machine learning protocol composed by network-based statistics and deep learning As such, when a correlation can be established, the dMRI assessment of connectivity could serve as a biomarker to guide rehabilitation strategies, early in the course of recovery, so that rehabilitation outcome can be improved.Researcher(s)
- Promoter: Yperzeele Laetitia
- Co-promoter: Saeys Wim
- Fellow: Van Hinsberg Amber
Research team(s)
Project type(s)
- Research Project
Can stroke survivors re-learn normal walking? Understanding functional recovery and effects of exoskeleton-assisted training.
Abstract
Animal models suggest a limited time window of increased repair activity in the brain during the first weeks after damage, for example after a stroke. Within this time window, responsiveness to therapy is increased suggesting that this is the optimal time to start intensive rehabilitation. In great contrast, early rehabilitation is experienced by stroke patients as a time of being physical inactive. This lack of rehabilitation might explain rather disappointing mobility outcome, since a great amount of stroke survivors struggle to achieve independent community ambulation. The World Health Organisation expects an increase to 1.5 million new cases of stroke per year in 2025. If innovation in rehabilitation cannot be provided, the increasing incidence of stroke will inevitably lead to a growing chronic stroke population and a great burden for our society. A novel therapeutic strategy is a wearable exoskeleton. This device allows an earlier initiation of more intensive rehabilitation as it assists patients in walking even if they are severely affected. This technology has the potential to change acute stroke rehabilitation from an inactive into a motivating, active time as it allows early training of meaningful activity. However, due to its recent development this type of therapy is not yet investigated. We aim to fill this gap with the proposed project by investigating the effectiveness of this approach and provide evidence on an optimal time window for rehabilitation.Researcher(s)
- Promoter: Truijen Steven
- Co-promoter: Saeys Wim
- Co-promoter: Yperzeele Laetitia
- Fellow: Schröder Jonas
Research team(s)
Project website
Project type(s)
- Research Project