Developing software solutions to monitor post-stroke rehabilitation and improve patient recovery Download PDF Copy

According to the study 'The impact of stroke in Europe', by King's College for the European Stroke Alliance, between 2015 and 2035 there will be a 34% increase in the number of cases in Europe (up to 819,771). And in Spain, more than 100,000 people suffer from it (50% have disabling sequelae or die). Therefore, if prevention is fundamental, rehabilitation becomes a decisive factor in survival and quality of life.

The MAESTRO project ('New machine learning techniques to improve the prediction of post-stroke outcomes') focuses on solving the lack of reliable systems to monitor patient adherence to rehabilitation, as well as the effectiveness of the process. IMDEA Networks is the beneficiary of this EU-funded project (H2020-MSCA-IF-2020 - Marie Skłodowska Curie Individual Global Grant), running from March 2022 to February 2025, with Antonio Fernández Anta as principal investigator on behalf of the IMDEA Networks team. The project is in line with the H2020 objectives in Area III (digitization, research, and innovation) as well as in healthcare.

The researcher Augusto García-Agúndez will work at Brown University (USA) for the first two years, and the last one at the Madrid institution. In this context, the experience of working in the emergency department with biosensors and gamification, the experience in outlier detection and machine learning of IMDEA Networks, and the knowledge in deep learning applied to medicine of the AI Lab at Brown University are combined to develop algorithms capable of determining adherence to rehabilitation and its effectiveness using wearables. This will optimize rehabilitation and predict recovery by providing information to both the neurology team and feedback to patients and caregivers.

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