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On Supporting Parkinson's Disease Patients: The i-Prognosis Personalized Game Suite Design Approach

Authors: Sofia B. Dias; Evangelos Konstantinidis; José A. Diniz; Panagiotis D. Bamidis; Vassilios S. Charisis; Stelios Hadjidimitriou; Michael Stadtschnitzer; +5 Authors

On Supporting Parkinson's Disease Patients: The i-Prognosis Personalized Game Suite Design Approach

Abstract

The use of serious games in health care interventions sector has grown rapidly in the last years, however, there is still a gap in the understanding on how these types of interventions are used for the management of the Parkinson Disease (PD), in particular. Targeting intelligent early detection and intervention in PD area, the Personalized Game Suite (PGS) design process approach is presented as part of the H2020 i-PROGNOSIS project that introduces the integration of different serious games in a unified platform (i.e., ExerGames, DietaryGames, EmoGames, and Handwriting/Voice Games). From the methodological point of view, to facilitate the visualization of 14 game-scenarios, the system interface and the PD contexts, the storyboarding technique was adopted here. Overall, the realization of the PGS sets the basis for establishing a holistic framework that could aim at improving motor and non-motor symptoms, in order to inform health care providers and policy makers for its inclusion in routine management for PD.

Keywords

Personalized Game Suite, i-PROGNOSIS, Parkinson's Disease, Storyboards

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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