Objective
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.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
- engineering and technologymedical engineeringdiagnostic imagingcomputed tomography
- engineering and technologyelectrical engineering, electronic engineering, information engineeringinformation engineeringtelecommunicationsmobile phones
- engineering and technologymedical engineeringdiagnostic imagingmagnetic resonance imaging
- medical and health sciencesbasic medicineneurologyparkinson
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
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Keywords
Programme(s)
Topic(s)
Call for proposal
(opens in new window) H2020-PHC-2014-2015
See other projects for this callSub call
H2020-PHC-2015-single-stage
Funding Scheme
RIA - Research and Innovation actionCoordinator
546 36 THESSALONIKI
Greece