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HoloPrognosis - An AR-Based Serious Exercise Game for Early Stage Parkinson’s Disease Patients

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Universal Access in Human-Computer Interaction. Design Approaches and Supporting Technologies (HCII 2020)

Abstract

Augmented Reality (AR) is a novel technology that experiences rapid bloom in the last years. By using an AR electronic device, we can blend the real world with a virtual one in real time. Gamification in healthcare interventions helps patients adopt a healthier lifestyle in various aspects of their lives. In this direction, there is ample space for exploration in the field of alternative treatments for diseases like Parkinson’s disease (PD). Among the various game categories targeting PD patients’ rehabilitation, exergames, that focus on the main exercises employed in the interventions phase of early-stage PD patients, gain great popularity. The reason is that physical activity is a key concept for delaying motor and functional loss of early-stage PD patients.

In this context, this work presents HoloPrognosis, an AR-based serious exercise game targeting the mitigation of upper limbs motor impairment of early-stage PD patients. More specifically, the game motivates the patients to reach large amplitude movements progressively while tracking their performance and collecting data related to hand movement for further analysis. Unlike other similar efforts, AR offers the advantages of augmented engagement and user experience, real first-person experience and authentic human body controls.

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Acknowledgements

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 690494.

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Correspondence to Vasileios Charisis .

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Thomos, M., Charisis, V., Hadjidimitriou, S., Iakovakis, D., Bostantzopoulou, S., Hadjileontiadis, L. (2020). HoloPrognosis - An AR-Based Serious Exercise Game for Early Stage Parkinson’s Disease Patients. In: Antona, M., Stephanidis, C. (eds) Universal Access in Human-Computer Interaction. Design Approaches and Supporting Technologies. HCII 2020. Lecture Notes in Computer Science(), vol 12188. Springer, Cham. https://doi.org/10.1007/978-3-030-49282-3_30

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  • DOI: https://doi.org/10.1007/978-3-030-49282-3_30

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-49281-6

  • Online ISBN: 978-3-030-49282-3

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