Personal and Ubiquitous Computing

, Volume 17, Issue 6, pp 1073–1083 | Cite as

Elderly frailty detection by using accelerometer-enabled smartphones and clinical information records

  • Jesús Fontecha
  • Fco. Javier Navarro
  • Ramón Hervás
  • José Bravo
Original Article

Abstract

Elderly people become weak until they reach a state of frailty. At this time, their health begins to get worse and they are more likely to suffer bone fractures, disorders, and diseases, and they become dependent. Delaying or reducing frailty level is important to improve the quality of life of elderly people. There are many parameters to consider for frailty detection and diagnosis. In this sense, assessment of physical condition, through gait and other physical exercises, is the most important domain in frailty evaluation. Nowadays, geriatricians and physiotherapists use several tests and scales based on indicators to provide scores related to physical assessment. However, these scores depend on the viewpoint of the geriatrician. So, the assessment contains a level of subjectivity. Besides, frailty detection includes the study of other indicators from nutritional, cognitive, and social domains. In this paper, we propose a system to support physicians determining an accurate and centralized elderly frailty diagnosis, by using an accelerometer-enabled mobile phone. The accelerometer collects data movement from physical activity and calculates a set of measures that are combined with clinical indicators (from tests and medical instruments) providing a frailty assessment to facilitate decision-making and the subsequent treatment.

Keywords

Frailty Elderly Healthcare Mobile computing Accelerometer 

Notes

Acknowledgments

This work has been financed by the TIN2010-20510-C04-04 project from the Ministerio de Ciencia e Innovación (Spain).

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Copyright information

© Springer-Verlag London Limited 2012

Authors and Affiliations

  • Jesús Fontecha
    • 1
  • Fco. Javier Navarro
    • 2
  • Ramón Hervás
    • 1
  • José Bravo
    • 1
  1. 1.MAmI Research LabCastilla-La Mancha UniversityCiudad RealSpain
  2. 2.Residencia Asistida de AncianosGeriatric ServiceCiudad RealSpain

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