Descripción del proyecto
Algoritmos para una rehabilitación efectiva del accidente cerebrovascular
Solo en 2015, se produjeron 600 000 accidentes cerebrovasculares en Europa. En tanto que uno de los problemas sanitarios más importantes en Europa, los accidentes cerebrovasculares requieren una rehabilitación estricta. Por desgracia, en la actualidad, carecemos de métodos que midan de manera efectiva el progreso y los resultados del tratamiento en los pacientes. El proyecto financiado con fondos europeos MAESTRO desarrollará algoritmos que permitan la evaluación de la efectividad de la rehabilitación y su optimización usando dispositivos ponibles (aplicaciones móviles y dispositivos de internet de las cosas). La innovación radica en las novedosas técnicas de aprendizaje automático (aprendizaje profundo), que permiten la clasificación automatizada de datos especialmente complejos, y una extracción pionera de información vital de conjuntos de datos para proporcionar a médicos, pacientes y cuidadores niveles de información específicos para cada grupo. MAESTRO está totalmente en consonancia con los objetivos de la tercera área de Horizonte 2020: digitalización, investigación e innovación.
Objetivo
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.
Ámbito científico
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Régimen de financiación
MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF)Coordinador
28918 Leganes (Madrid)
España