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    m-SFT: A Novel Mobile Health System to Asses the Elderly Physical Condition

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    This is an Open Access article (3.195Mb)
    Date
    2020-03-06
    Author
    Chiclana, Francisco;
    Gonzalez-Alvarez, Alvaro;
    Herrera-Viedma, Enrique;
    Moral-Munoz, Jose A.;
    Urena, Raquel
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    Abstract
    The development of innovative solutions that allow the aging population to remain healthier and independent longer is essential to alleviate the burden that this increasing segment of the population supposes for the long term sustainability of the public health systems. It has been claimed that promoting physical activity could prevent functional decline. However, given the vulnerability of this population, the activity prescription requires to be tailored to the individual’s physical condition. We propose mobile Senior Fitness Test (m-SFT), a novel m-health system, that allows the health practitioner to determine the elderly physical condition by implementing a smartphone-based version of the senior fitness test (SFT). The technical reliability of m-SFT has been tested by carrying out a comparative study in seven volunteers (53–61 years) between the original SFT and the proposed m-health system obtaining high agreement (intra-class correlation coefficient (ICC) between 0.93 and 0.99). The system usability has been evaluated by 34 independent health experts (mean = 36.64 years; standard deviation = 6.26 years) by means of the System Usability Scale (SUS) obtaining an average SUS score of 84.4 out of 100. Both results point out that m-SFT is a reliable and easy to use m-health system for the evaluation of the elderly physical condition, also useful in intervention programs to follow-up the patient’s evolution.
    Description
    open access article
    Citation : Ureña, R., Chiclana, F., Gonzalez-Alvarez, A., Herrera-Viedma, E., Moral-Munoz, J.A. (2020) m-SFT: A Novel Mobile Health System to Asses the Elderly Physical Condition. Sensors, 20(5), pp.1462.
    URI
    https://dora.dmu.ac.uk/handle/2086/19404
    DOI
    https://doi.org/10.3390/s20051462
    Research Institute : Institute of Artificial Intelligence (IAI)
    Peer Reviewed : Yes
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    • School of Computer Science and Informatics [2970]

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