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Report

Teaser, summary, work performed and final results

Periodic Reporting for period 1 - i-PROGNOSIS (Intelligent Parkinson eaRly detectiOn Guiding NOvel Supportive InterventionS)

Teaser

Summary

Parkinsonâ€™s Disease (PD) is one of the commonest neurodegenerative diseases, affecting approximately 1% of individuals older than 60 years and 2-4% over than 75 years, causing progressive disability that results in a burden of ~2.2 million disability-adjusted life years (DALYs), exhibiting the greatest loss of quality-adjusted life years (QALYs) among 29 major chronic conditions. PD is a progressive and chronic neurological disease that often begins with mild symptoms in walking, talking and writing, emotional stability, that advance gradually over time. Symptoms can be so subtle in the early stages that they go unnoticed, as there are no PD-related biomarkers (e.g., blood tests) and findings on routine magnetic resonance imaging and computed tomography scans are unremarkable, leaving the disease undiagnosed for years. Motivated by the aforementioned, i-PROGNOSIS proposes an intelligent ICT-based approach for early PD symptoms detection and early intervention in older adultâ€™s everyday life, promoting active and healthy ageing, by introducing new ways of health self-managing tools, set within a collaborative care context with health professionals. The overall objectives of i-PROGNOSIS are: i) the introduction of new early diagnostic tests for PD symptoms based on features extracted from securely Cloud-stored behavioural and sensorial data, unobtrusively collected by smart devices (e.g., smartphone, smartwatch), wearable biosensors and IoT-based everyday living sensorial artefacts, and processed by advanced big data analytics and machine learning techniques, ii) design and implementation of novel ICT-based adaptive, gamified, and personalized interventions, along with assistive interventions, taking into account older adultâ€™s physical and psychological status, promoting his/her health self-management at the family setting by providing dynamic feedback towards the improvement of older adultâ€™s skills and functionalities for reduction of the PD-related risks of frailty, depression and falls, and iii) fostering of social awareness for volunteerism in early PD detection and construction of socio-economic and informed behavioural models for new cost-effective ICT-based PD early detection and related risks-reduction intervention practices and policies for the sustainability of health and care systems and the benefit of the older adults.

Work performed

The reporting period spans from M1 up to M12 (1st year of the project) and the work performed along with the main results achieved within this period refer to the: establishment of a solid collaboration basis between all partners of the consortium, ensuring quality, timely reporting, financial thoroughness and transparency following a detailed management plan that clearly defines the management hierarchy, roles and responsibilities of all involved parties, in conjunction with a functional and efficient Quality Assessment Plan (WP1); identification of the user requirements connected with the i-PROGNOSIS architecture, usages scenarios and business services, along with the specification of the data collection and medical evaluation protocols governing all phases of data collection and system evaluation during the project lifespan via collaborative efforts of i-PROGNOSIS medical and technical partners (WP2); design and implementation of the data acquisition (capturing) methods, along with development of initial prototypes of the data acquisition devices (e.g., Smart Belt) and implementation of a first version of the feature extraction and machine learning algorithms (WP3); conceptual design of the first version of personalised serious game suite for the interventions phase, proposing 14 (in total) different storyboards, including PD patients as co-designers/creators in the first comprehensive draft of the games (WP4); realisation of the first mobile i-PROGNOSIS application for acquiring data from the everyday use of the smartphone, archived in the Cloud, governed by the introduced Data Management Plan (WP5); design and first application of detailed and holistic assessment plan and evaluation methodology (WP7); scaffolding of social awareness via dissemination activities towards the i-PROGNOSIS community construction, informing the relevant network of stakeholders, and gradually structuring social penetration and exploring opportunities for Intellectual Property Rights (IPR) exploitation (WP8). The described workload and results, clearly support the three basic pillars of i-PROGNOSIS, i.e., PD early detection, novel PD-related interventions and social responsiveness to participation, data donation and PD awareness.

Final results

The progress beyond the state-of-the-art of the i-PROGNOSIS so far refers to aspects of its three pillars. In particular, for the PD early detection, a first version of the mobile i-PROGNOSIS application, incorporating a novel smart keyboard, for unobtrusively acquiring the GData from the everyday use of the smartphone, archived in the Cloud, has been constructed for the first time. In addition to this, a smart belt for noninvasively capturing the bowel sounds and, thus, monitoring constipation, was constructed, facilitating SData acquisition. The impact of this is the offering of the innovative possibility to undertake large-scale, accurate, longitudinal health-based research - â€œcrowd sourced researchingâ€ towards the introduction of PD predictors. This is used to generate large amounts of data previously unavailable as part of a knowledge base health economy for any company in the broad domains of ageing/health/lifestyle/fitness (i.e., Silver Market) in the unified Digital Market, as well as providing an ecologically valid alternative for costly random controlled trials. For the PD novel interventions, the scenarios of a holistic personalized serious game suite were initially designed, encapsulating, for the first time, the most profound intervention activities for PD patients, via the gamified environment of ExerGames, DietaryGames, Handwriting/Voice Games and EmoGames. This provides the opportunity for home-based, patient-centric interventions that target the PD-related risks of frailty, falls and depression, via lifestyle behavioural change program and places a positive impact to them improving the experience of living with PD, enabling better self-manage of their health status through key interdependent modules (social interaction, peer mentoring, behavioural change, gamified physical/emotional adherence), serving as a powerful and compelling approach to sustainable healthcare and active and healthy ageing. For the PD social awareness, a core mass of the i-PROGNOSIS community has been established for the first time, via the dissemination activities undertaken so far, providing the basis to deploy the novel acquisition tools (e.g., mobile i-PROGNOSIS application) and increase the social responsiveness to data donation and participation in the healthy and active ageing initiatives, such as i-PROGNOSIS. The stakeholders networking achieved so far, tries to evoke the transformation from an â€œI thinkâ€ culture to a â€œwe knowâ€ culture, leading to more informed and validated interventions supporting active and healthy ageing back to the community and society, as its extension. This closes the feedback loop and increases levels of older adultsâ€™ and stakeholdersâ€™ engagement, allowing them to understand that their participation actually makes a difference to how the early PD prediction progresses.