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Sensitivity and specificity of fall detection in people aged 40 years and over
University of Oulu.
Luleå University of Technology, Department of Health Sciences, Health and Rehabilitation.ORCID iD: 0000-0002-1682-8326
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab.
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab.
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2009 (English)In: Gait & Posture, ISSN 0966-6362, E-ISSN 1879-2219, ISSN 0966-6362, Vol. 29, no 4, p. 571-574Article in journal (Refereed) Published
Abstract [en]

About one third of home-dwelling people over 65 years of age fall each year. Falling, and the fear of falling, is one of the major health risks that affects the quality of life among older people, threatening their independent living. In our pilot study, we found that fall detection with a waist-worn triaxial accelerometer is reliable with quite simple detection algorithms. The aim of this study was to validate the data collection of a new fall detector prototype and to define the sensitivity and specificity of different fall detection algorithms with simulated falls from 20 middle-aged (40-65 years old) test subjects. Activities of daily living (ADL) performed by the middle-aged subjects, and also by 21 older people (aged 58-98 years) from a residential care unit, were used as a reference. The results showed that the hardware platform and algorithms used can discriminate various types of falls from ADL with a sensitivity of 97.5% and a specificity of 100%. This suggests that the present concept provides an effective method for automatic fall detection.

Place, publisher, year, edition, pages
2009. Vol. 29, no 4, p. 571-574
Keywords [en]
Caring sciences, Physiotherapy
Keywords [sv]
Vårdvetenskap, Sjukgymnastik/fysioterapi
National Category
Physiotherapy Embedded Systems
Research subject
Physiotherapy; Embedded Systems; Centre - eHealth Innovation Centre (EIC)
Identifiers
URN: urn:nbn:se:ltu:diva-12320DOI: 10.1016/j.gaitpost.2008.12.008ISI: 000265476000010Scopus ID: 2-s2.0-63249132839Local ID: b6fed820-f487-11dd-a323-000ea68e967bOAI: oai:DiVA.org:ltu-12320DiVA, id: diva2:985270
Note

Validerad; 2009; 20090206 (ysko)

Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2019-03-20Bibliographically approved

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Vikman, IreneWiklander, JimmieLindgren, PerNyberg, Lars

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