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Novel machine learning techniques to improve the forecasting of stroke post-interventive outcomes

Descrizione del progetto

Algoritmi per un’efficace riabilitazione post-ictus

In Europa, solo nel 2015 si sono verificati 600 000 ictus. In quanto problema sanitario di alto livello in questo continente, esso richiede una riabilitazione rigorosa. Sfortunatamente, vi è al momento una carenza di metodi in grado di misurare in modo efficace i progressi compiuti dai pazienti e i risultati ottenuti dai trattamenti. Il progetto MAESTRO, finanziato dall’UE, svilupperà algoritmi che consentono di effettuare una valutazione dell’efficacia della riabilitazione, nonché di ottimizzarla mediante l’impiego di dispositivi indossabili (applicazioni mobili e dispositivi IoT). L’innovazione consiste in nuove tecniche di apprendimento automatico (apprendimento profondo) che permettono una classificazione automatizzata di dati particolarmente complessi e in un’estrazione pionieristica di informazioni vitali dai set di dati allo scopo di fornire a medici, pazienti e assistenti livelli di feedback specifici in base al gruppo. MAESTRO si allinea completamente con gli obiettivi di Orizzonte 2020 rientranti nell’Area III, ovvero digitalizzazione, ricerca e innovazione.

Obiettivo

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.

Coordinatore

FUNDACION IMDEA NETWORKS
Contribution nette de l'UE
€ 245 732,16
Indirizzo
AVENIDA DEL MAR MEDITERRANEO 22
28918 Leganes (Madrid)
Spagna

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Regione
Comunidad de Madrid Comunidad de Madrid Madrid
Tipo di attività
Research Organisations
Collegamenti
Costo totale
€ 245 732,16

Partner (1)