Description du projet
Des algorithmes pour une rééducation post-AVC efficace
Rien qu’en 2015, 600 000 accidents vasculaires cérébraux se sont produits en Europe. En tant que problème de santé de premier plan en Europe, l’accident vasculaire cérébral nécessite une rééducation stricte. Malheureusement, on constate actuellement un manque de méthodes permettant de mesurer efficacement les progrès et les résultats des patients en traitement. Le projet MAESTRO, financé par l’UE, développera des algorithmes permettant d’évaluer l’efficacité de la rééducation et de l’optimiser en utilisant des dispositifs portables (applications mobiles et dispositifs IdO). L’innovation réside dans les nouvelles techniques d’apprentissage automatique (apprentissage profond), qui permettent la classification automatisée de données particulièrement complexes, et dans l’extraction inédite d’informations vitales à partir d’ensembles de données afin de fournir aux médecins, aux patients et aux soignants des niveaux de retour d’information spécifiques à un groupe. MAESTRO s’inscrit pleinement dans les objectifs d’Horizon 2020 du domaine III – numérisation, recherche et innovation.
Objectif
Stroke is a first-order medical problem (about 600,000 strokes occurred in the EU in 2015), in which rehabilitation is critical. Currently, there are no reliable systems to monitor the patient adherence to this rehabilitation, nor its effectiveness. Combining the ER experience on biosensors and gamification, the expertise on outlier detection and machine learning of IMDEA Networks, and the knowledge on deep learning applied to medicine of the AI Lab at Brown University, in MAESTRO, we will develop algorithms capable of determining rehabilitation adherence and effectiveness by using wearables. This will optimize rehabilitation and forecast recovery by providing information to neurologists and feedback to patients and caregivers. MAESTRO aligns with the H2020 goals in Area III (digitization, research and innovation) as well as health, demographic change, and wellbeing.
MAESTRO aims at recruiting 50 patients from Rhode Island Hospital for 4 months in the first of three development cycles. Mobile applications, IoT devices and questionnaires will be used in the first of the three cycles. This is viable since we will use the infrastructure and connections of an existing stroke project on-site.
The innovation in MAESTRO lays in the development of software solutions to monitor the rehabilitation of post-stroke patients remotely and passively using off-the-shelf hardware and gamification. The methods employed in MAESTRO, particularly deep learning, permit the automated classification of extremely complex data, allowing scientists to extract important information from data sets that would be unmanageable otherwise.
MAESTRO is a unique scientific advance because it will provide doctors, patients and caregivers, group-specific levels of feedback. In addition, the algorithms specifically developed within the project can be the bases of novel developments with different goals, for example translation to clinical practice, or expansion to other neurodegenerative diseases.
Champ scientifique
Mots‑clés
Programme(s)
Régime de financement
MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF)Coordinateur
28918 Leganes (Madrid)
Espagne