Research Article
Analytic Hierarchy Process for assessing e-health technologies for elderly indoor mobility analysis
@INPROCEEDINGS{10.4108/eai.14-10-2015.2261667, author={Simona Lohan and Oana Cramariuc and Łukasz Malicki and Neja Samar Brenčič and Bogdan Cramariuc}, title={Analytic Hierarchy Process for assessing e-health technologies for elderly indoor mobility analysis}, proceedings={5th EAI International Conference on Wireless Mobile Communication and Healthcare - "Transforming healthcare through innovations in mobile and wireless technologies"}, publisher={ACM}, proceedings_a={MOBIHEALTH}, year={2015}, month={12}, keywords={analytic hierarchy process (ahp) elderly e-health care fall detection indoor mobility user surveys}, doi={10.4108/eai.14-10-2015.2261667} }- Simona Lohan
Oana Cramariuc
Łukasz Malicki
Neja Samar Brenčič
Bogdan Cramariuc
Year: 2015
Analytic Hierarchy Process for assessing e-health technologies for elderly indoor mobility analysis
MOBIHEALTH
ICST
DOI: 10.4108/eai.14-10-2015.2261667
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.
