Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Real-time constant monitoring of fall risk index by means of fully-wireless insoles
Spring Techno GmbH & Co, Germany..
Spring Techno GmbH & Co, Germany..
Universitat Autònoma de Barcelona, Spain.
Universitat Autònoma de Barcelona, Spain.
Show others and affiliations
2017 (English)Conference paper, Published paper (Refereed)
Abstract [en]

Constant monitoring of gait in real life conditions is considered the best way to assess Fall Risk Index (FRI) since most falls happen out of the ideal conditions in which clinicians are currently analyzing the patient's behavior. This paper presents the WIISEL platform and results obtained through the use of the first full-wireless insole devices that can measure almost all gait related data directly on the feet (not in the upper part of the body as most existing wearable solutions). The platform consists of a complete tool-chain: insoles, smartphone & app, server & analysis tool, FRI estimation and user access. Results are obtained by combining parameters in a personalized way to build individual fall risk index assessed by experts with the help of data analytics. New FRI has been compared with standards that validate the quality of its prediction in a statistically significant way. That qualitatively relevant information is being provided to the platform users, being either end-users/patients, relatives or caregivers and the related clinicians to ideally assess about their long term evolution. © 2017 The authors and IOS Press.

Place, publisher, year, edition, pages
2017. p. 193-197
Keywords [en]
Fall risk, Fall Risk Index (FRI), Gait analysis, Wireless insole, caregiver, doctor patient relation, foot, gait, human, monitoring, prediction, relative, smartphone
National Category
Natural Sciences
Identifiers
URN: urn:nbn:se:ri:diva-31175DOI: 10.3233/978-1-61499-761-0-193Scopus ID: 2-s2.0-85019478635ISBN: 9781614997603 (print)OAI: oai:DiVA.org:ri-31175DiVA, id: diva2:1135569
Conference
14th International Conference on Wearable Micro and Nano Technologies for Personalized Health, pHealth 2017. 14 May 2017 through 16 May 2017
Available from: 2017-08-23 Created: 2017-08-23 Last updated: 2023-05-16Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records

Rusu, Cristina

Search in DiVA

By author/editor
Rusu, Cristina
By organisation
Acreo
Natural Sciences

Search outside of DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 162 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf