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Phyx.io: Expert-Based Decision Making for the Selection of At-Home Rehabilitation Solutions for Active and Healthy Aging

Author

Listed:
  • Javier Dorado Chaparro

    (Computer Architecture and Networks Group, School of Computer Science, University of Castilla-La Mancha, 13071 Ciudad Real, Spain)

  • Jesús Fernández-Bermejo Ruiz

    (Computer Architecture and Networks Group, School of Computer Science, University of Castilla-La Mancha, 13071 Ciudad Real, Spain)

  • María José Santofimia Romero

    (Computer Architecture and Networks Group, School of Computer Science, University of Castilla-La Mancha, 13071 Ciudad Real, Spain)

  • Xavier del Toro García

    (Computer Architecture and Networks Group, School of Computer Science, University of Castilla-La Mancha, 13071 Ciudad Real, Spain)

  • Rubén Cantarero Navarro

    (Computer Architecture and Networks Group, School of Computer Science, University of Castilla-La Mancha, 13071 Ciudad Real, Spain)

  • Cristina Bolaños Peño

    (Computer Architecture and Networks Group, School of Computer Science, University of Castilla-La Mancha, 13071 Ciudad Real, Spain)

  • Henry Llumiguano Solano

    (Computer Architecture and Networks Group, School of Computer Science, University of Castilla-La Mancha, 13071 Ciudad Real, Spain)

  • Félix Jesús Villanueva Molina

    (Computer Architecture and Networks Group, School of Computer Science, University of Castilla-La Mancha, 13071 Ciudad Real, Spain)

  • Anabela Gonçalves Silva

    (Center for Health Technology and Services Research, Health Sciences School, University of Aveiro, 3810-193 Aveiro, Portugal)

  • Juan Carlos López

    (Computer Architecture and Networks Group, School of Computer Science, University of Castilla-La Mancha, 13071 Ciudad Real, Spain)

Abstract

While the importance of physical activity in older adults is beyond doubt, there are significant barriers limiting the access of older adults to physical exercise. Existing technologies to support physical activity in older adults show that, despite their positive impacts on health and well-being, there is in general a lack of engagement due to the existing reluctance to the use of technology. Usefulness and usability are two major factors for user acceptance along with others, such as cost, privacy, equipment and maintenance requirements, support, etc. Nevertheless, the extent to which each factor impacts user acceptance remains unclear. Furthermore, other stakeholders, besides the end users, should be considered in the decision-making process to develop such technologies, including caregivers, therapists and technology providers. In this paper, and in the context of physical rehabilitation and exercise at home, four different alternatives with incremental characteristics have been defined and considered: a software-based platform for physical rehabilitation and exercise (Alternative 1), the same software platform with a conventional RGB camera and no exercise supervision (Alternative 2), the same software platform with a convention RGB camera and exercise supervision (Alternative 3) and finally, the same software platform with a depth camera and exercise supervision (Alternative 4). A multiple attribute decision-making methodology, based on the ordinal priority approach (OPA) method, is then applied using a group of experts, including end users, therapists and developers to rank the best alternative. The attributes considered in this method have been usefulness, cost, ease of use, ease of technical development, ease of maintenance and privacy, concluding that Alternative 3 has been ranked as the most appropriate.

Suggested Citation

  • Javier Dorado Chaparro & Jesús Fernández-Bermejo Ruiz & María José Santofimia Romero & Xavier del Toro García & Rubén Cantarero Navarro & Cristina Bolaños Peño & Henry Llumiguano Solano & Félix Jesús , 2022. "Phyx.io: Expert-Based Decision Making for the Selection of At-Home Rehabilitation Solutions for Active and Healthy Aging," IJERPH, MDPI, vol. 19(9), pages 1-20, May.
  • Handle: RePEc:gam:jijerp:v:19:y:2022:i:9:p:5490-:d:807081
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    References listed on IDEAS

    as
    1. Javier Dorado & Xavier del Toro & Maria J Santofimia & Alfonso Parreño & Ruben Cantarero & Ana Rubio & Juan C Lopez, 2019. "A computer-vision-based system for at-home rheumatoid arthritis rehabilitation," International Journal of Distributed Sensor Networks, , vol. 15(9), pages 15501477198, September.
    2. Bram Constandt & Erik Thibaut & Veerle De Bosscher & Jeroen Scheerder & Margot Ricour & Annick Willem, 2020. "Exercising in Times of Lockdown: An Analysis of the Impact of COVID-19 on Levels and Patterns of Exercise among Adults in Belgium," IJERPH, MDPI, vol. 17(11), pages 1-10, June.
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