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Open AccessArticle

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

1
Institute of Artificial Intelligence (IAI), School of Computer Science and Informatics, De Montfort University, Leicester LE1 9BH, UK
2
Andalusian Research Institute on Data Science and Computational Intelligence (DaSCI), University of Granada, 18071 Granada, Spain
3
Department of Computer Science, University of Cadiz, 11519 Puerto Real, Spain
4
Department of Nursing and Physiotherapy, Universidad de Cádiz, 11009 Cádiz, Spain
5
Institute of Research and Innovation in Biomedical Sciences of the Province of Cádiz (INiBICA), Universidad de Cádiz, 11009 Cádiz, Spain
*
Author to whom correspondence should be addressed.
Sensors 2020, 20(5), 1462; https://doi.org/10.3390/s20051462
Received: 16 January 2020 / Revised: 1 March 2020 / Accepted: 2 March 2020 / Published: 6 March 2020
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. View Full-Text
Keywords: senior fitness test; physical condition; elderly; physical condition assessment; m-health; mobile health; healthy aging senior fitness test; physical condition; elderly; physical condition assessment; m-health; mobile health; healthy aging
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Ureña, R.; Chiclana, F.; Gonzalez-Alvarez, A.; Herrera-Viedma, E.; Moral-Munoz, J.A. m-SFT: A Novel Mobile Health System to Assess the Elderly Physical Condition. Sensors 2020, 20, 1462.

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