Obiettivo
Transition from healthy status to Parkinson’s Disease (PD) is vaguely tractable, since symptoms can be so subtle in the early stages that they go unnoticed. Lack of biomarkers and/or findings on routine MRI and CT scans, PD is left undiagnosed for years, gradually affecting the life of over 6.5 million of older adults (>55-60 yrs) worldwide, increasing the risk of their health deterioration. Epidemiological studies conclude that early intervention could have an inverse relation with the PD-related risks of progressive frailty, falls and emotional shift towards depression. Based on this evidence, the cardinal objective of i-PROGNOSIS is the development of (i) an ICT-based behavioural analysis approach for capturing, as early as possible, the PD symptoms appearance, and (ii) the application of ICT-based interventions countering identified risks. To achieve this, awareness initiatives will be employed, so as to construct i-PROGNOSIS community, targeting > 5000 older individuals within the duration of the project, in order to unobtrusively sense large scale behavioural data from its members, acquired from their natural use of mobile devices (smartphone/smartwatch). Ensuring anonymisation and secure Cloud archiving, i-PROGNOSIS will develop and employ advanced big data analytics and machine learning techniques, in a distributed and privacy aware fashion, so as to instantiate a PD Behavioural Model and construct reliable early PD symptoms detection alarms. To those identified and clinically validated as early stage PD patients, ICT-based interventions will be provided via the i-PROGNOSIS Intervention Platform, including: a) a Personalised Game Suite (ExerGames, DietaryGames, EmoGames, Handwriting/VoiceGames) for physical/emotional support, b) targeted nocturnal intervention to increase relaxation/sleep quality and c) assistive interventions for voice enhancement and gait rhythm guidance. In this way, i-PROGNOSIS will constructively contribute to active and healthy ageing.
Campo scientifico (EuroSciVoc)
CORDIS classifica i progetti con EuroSciVoc, una tassonomia multilingue dei campi scientifici, attraverso un processo semi-automatico basato su tecniche NLP.
CORDIS classifica i progetti con EuroSciVoc, una tassonomia multilingue dei campi scientifici, attraverso un processo semi-automatico basato su tecniche NLP.
- ingegneria e tecnologiaingegneria medicadiagnostica per immaginitomografia computerizzata
- ingegneria e tecnologiaingegneria elettrica, ingegneria elettronica, ingegneria informaticaingegneria informaticatelecomunicazionitelefoni mobili
- ingegneria e tecnologiaingegneria medicadiagnostica per immaginirisonanza magnetica per immagini
- scienze mediche e della salutemedicina di baseneurologiaparkinson
- scienze naturaliinformatica e scienze dell'informazioneintelligenza artificialeapprendimento automatico
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Parole chiave
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Invito a presentare proposte
Vedi altri progetti per questo bandoBando secondario
H2020-PHC-2015-single-stage
Meccanismo di finanziamento
RIA - Research and Innovation actionCoordinatore
546 36 THESSALONIKI
Grecia