Literature DB >> 21133771

Defining the user requirements for wearable and optical fall prediction and fall detection devices for home use.

Mehmet Gövercin1, Y Költzsch, M Meis, S Wegel, M Gietzelt, J Spehr, S Winkelbach, M Marschollek, E Steinhagen-Thiessen.   

Abstract

One of the major problems in the development of information and communication technologies for older adults is user acceptance. Here we describe the results of focus group discussions that were conducted with older adults and their relatives to guide the development of assistive devices for fall detection and fall prevention. The aim was to determine the ergonomic and functional requirements of such devices and to include these requirements in a user-centered development process. A semi-structured interview format based on an interview guide was used to conduct three focus group discussions with 22 participants. The average age was 75 years in the first group, 68 years in the second group and 50 years in the third group (relatives). Overall, participants considered a fall prediction system to be as important as a fall detection system. Although the ambient, unobtrusive character of the optical sensor system was appreciated, wearable inertial sensors were preferred because of their wide range of use, which provides higher levels of security. Security and mobility were two major reasons for people at risk of falling to buy a wearable and/or optical fall prediction and fall detection device. Design specifications should include a wearable, non-stigmatising sensor at the user's wrist, with an emergency option in case of falling.

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Year:  2010        PMID: 21133771     DOI: 10.3109/17538157.2010.528648

Source DB:  PubMed          Journal:  Inform Health Soc Care        ISSN: 1753-8157            Impact factor:   2.439


  7 in total

1.  GAL@Home: a feasibility study of sensor-based in-home fall detection.

Authors:  M Gietzelt; J Spehr; Y Ehmen; S Wegel; F Feldwieser; M Meis; M Marschollek; K-H Wolf; E Steinhagen-Thiessen; M Gövercin
Journal:  Z Gerontol Geriatr       Date:  2012-12       Impact factor: 1.281

Review 2.  Fall detection devices and their use with older adults: a systematic review.

Authors:  Shomir Chaudhuri; Hilaire Thompson; George Demiris
Journal:  J Geriatr Phys Ther       Date:  2014 Oct-Dec       Impact factor: 3.381

3.  Advancing the Aging and Technology Agenda in Gerontology.

Authors:  Richard Schulz; Hans-Werner Wahl; Judith T Matthews; Annette De Vito Dabbs; Scott R Beach; Sara J Czaja
Journal:  Gerontologist       Date:  2014-08-27

Review 4.  Involvement of older people in the development of fall detection systems: a scoping review.

Authors:  Friederike J S Thilo; Barbara Hürlimann; Sabine Hahn; Selina Bilger; Jos M G A Schols; Ruud J G Halfens
Journal:  BMC Geriatr       Date:  2016-02-11       Impact factor: 3.921

5.  Feasibility of Sensor Technology for Balance Assessment in Home Rehabilitation Settings.

Authors:  Daniel Kelly; Karla Muñoz Esquivel; James Gillespie; Joan Condell; Richard Davies; Shvan Karim; Elina Nevala; Antti Alamäki; Juha Jalovaara; John Barton; Salvatore Tedesco; Anna Nordström
Journal:  Sensors (Basel)       Date:  2021-06-28       Impact factor: 3.576

Review 6.  Review of fall risk assessment in geriatric populations using inertial sensors.

Authors:  Jennifer Howcroft; Jonathan Kofman; Edward D Lemaire
Journal:  J Neuroeng Rehabil       Date:  2013-08-08       Impact factor: 4.262

7.  Parkinson's disease: current assessment methods and wearable devices for evaluation of movement disorder motor symptoms - a patient and healthcare professional perspective.

Authors:  Ghayth AlMahadin; Ahmad Lotfi; Eva Zysk; Francesco Luke Siena; Marie Mc Carthy; Philip Breedon
Journal:  BMC Neurol       Date:  2020-11-18       Impact factor: 2.474

  7 in total

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