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:
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:
In this way, i-PROGNOSIS will constructively contribute to active and healthy ageing.