The focus of this project is to develop a novel home-based exergaming system aimed at enhancing resistance to falls among individuals post-stroke. Preventing falls and fall-related injuries, minimizes healthcare utilization and societal costs and supports stroke survivors in maintaining independence in daily life.

The Research
The HEROES system is designed to target balance perturbations and improve stepping responses. It utilizes action observation and motor imagery techniques to personalize training for individuals with stroke. Stroke survivors will undergo a single training session in a rehabilitation center to practice recovering from real balance perturbations before using HEROES at home.

The effectiveness of the HEROES-system will be assessed through a proof-of-principle randomized controlled trial (RCT) involving 60 stroke survivors, evaluating its impact on fall resistance and balance enhancement post-stroke. The approach of involving stroke survivors sets HEROES clearly apart from the currently available home-based exergames, which uses ‘healthy’ people and lack the required personalization of different post-stroke individuals.

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Contact person:

Prof. dr. V. Weerdesteyn (Vivian)

Principal investigators

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Smoking tobacco and physical inactivity are key preventable risk factors of cardiovascular disease (CVD). Perfect Fit aims to prevent CVD, promote well-being, and reduce healthcare costs, particularly targeting disadvantaged populations where smoking and physical inactivity are prevalent. The Research The project develops tailored, evidence-based, near real-time computer coaching for quitting smoking and enhancing PA. For every individual, a personal model is designed which generates personalized recommendations based on high-quality existing and newly collected data, and adapts to changing circumstances/progress (similar to a TomTom navigation system), using machine learning techniques and incorporating domain-specific expert knowledge (e.g. health behaviour change strategies). Virtual coaches (VCs) communicate advice in a motivating way that fits individuals’ persuasive communication styles. Perfect Fit integrates big-data science, sensor technology, and personalized real-time feedback to support smoking cessation and promote adequate physical activity (in both gym settings and daily life). The key questions of this study are: Which adaptivity is needed to create a robust, safe, and effective interaction between individuals and machines? How can we develop advanced data science methods and embed this in current smoking cessation and PA coaching practice? How do measurement modalities, feedback and communication affect individuals’ smoking status and PA?  
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