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Analytic Hierarchy Process for assessing e-health technologies for elderly indoor mobility analysis

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Details

Original languageEnglish
Title of host publicationMOBIHEALTH 2015
Subtitle of host publication5th EAI International Conference on Wireless Mobile Communication and Healthcare - "Transforming healthcare through innovations in mobile and wireless technologies"
Place of PublicationLondon
PublisherICST
Number of pages4
ISBN (Electronic)978-1-63190-088-4
Publication statusPublished - Oct 2015
Publication typeA4 Article in a conference publication
EventInternational ICST Conference on Wireless Mobile Communication and Healthcare -
Duration: 1 Jan 1900 → …

Conference

ConferenceInternational ICST Conference on Wireless Mobile Communication and Healthcare
Period1/01/00 → …

Abstract

Accidental falls and reduced mobility are major risk factors in later life. Changes in a person’s mobility patterns can be related with personal well-being and with the frequency of memory lapses and can be used as risk detectors of incipient neuro-degenerative diseases. Thus, developing technologies for fall detection and indoor localization and novel methods for mobility pattern analysis is of utmost importance in e-health. Choosing the right technology is not only a matter of cost and performance, but also a matter of user acceptability and the perceived ease-of-use by the end user. In this paper, we employ an Analytic Hierarchy Process (AHP) to assess the best fit-to-purpose technology for fall detection and user mobility estimation. Our multi-criteria decision making process is based on the survey results collected from 153 elderly volunteers from 5 EU countries and on 10 emerging e-health technologies for fall detection and indoor mobility pattern estimation. Our analysis points out towards a Bluetooth Low Energy wearable solution as the most suitable solution.