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The Use of Gamification Techniques in a Clinical Setting for the Collection of Longitudinal Kinematic Data

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Ubiquitous Computing and Ambient Intelligence (UCAmI 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10069))

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Abstract

Children with physical impairments, ranging from impaired mobility to very limited mobility, often require mobility aids to compensate for these difficulties. These impairments can adversely affect the child to varying degrees and have an impact on their health and wellbeing. It is estimated that 30 %–40 % of medical interventions have no reported evidence base and another 20 % of interventions delivered are ineffective. Clinicians are under increasing pressure to provide evidence of the effectiveness of prescribed treatments and products. Therefor there is a need to provide clinicians with empirical data that evidences practice and provides a quantified assessment of treatment efficacy through data gathering in both real-time and longitudinally, combined with data analytics to further develop treatment strategies. This paper presents a system to assist and enable clinicians to analyze and asses the effectiveness and usage of prescribed treatments for physically impaired children. The system achieves this through the use of a gamified data collection app and a web portal to analyze and present summarized measures of gait.

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Acknowledgments

Invest Northern Ireland is acknowledged for supporting this project under the Competence Centre Programs Grant RD0513853 – Connected Health Innovation Centre.

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Correspondence to Andrew Ennis .

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Ennis, A., Cleland, I., Nugent, C., Finney, L., Trainor, D., Bennett, A. (2016). The Use of Gamification Techniques in a Clinical Setting for the Collection of Longitudinal Kinematic Data. In: García, C., Caballero-Gil, P., Burmester, M., Quesada-Arencibia, A. (eds) Ubiquitous Computing and Ambient Intelligence. UCAmI 2016. Lecture Notes in Computer Science(), vol 10069. Springer, Cham. https://doi.org/10.1007/978-3-319-48746-5_27

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  • DOI: https://doi.org/10.1007/978-3-319-48746-5_27

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-48745-8

  • Online ISBN: 978-3-319-48746-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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