Sway Risk Analysis Based on Age Group Classification

Hafsa Ismail, Ibrahim Radwan, Hanna Suominen, Gordon Waddington, Roland Goecke

Research output: A Conference proceeding or a Chapter in BookConference contributionpeer-review

Abstract

Human postural sway is the horizontal movement, which is generated to control a person’s balance while walking or standing. Changes in postural sway patterns are a reflection of changes in brain signals and in physical health affected by a person’s aging process. This increases the likelihood of falling. In this paper, we propose a method to estimate the age groups of elderly people based on the extracted sway measurements. These measurements are computed based on learning the postural sway signal from video footage only. Then, we use the person’s real age and the estimated age group to define a risk of a fall for the elderly people becoming more likely. This may lead to an early intervention and help them to prevent serious falls or injuries by putting countermeasures in place, e.g. physical exercise regimes. The conducted experiments show the reliability of the proposed method to produce a risk analysis tool for elderly based on their estimated sway signals.
Original languageEnglish
Title of host publication2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
EditorsRiccardo Barbieri
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages392-398
Number of pages7
ISBN (Electronic)9781538613115
ISBN (Print)9781538613122
DOIs
Publication statusPublished - 2019
Event41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) - Berlin, Germany
Duration: 23 Jul 201927 Jul 2019
https://embc.embs.org/2019/

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN (Print)1557-170X

Conference

Conference41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Abbreviated titleEMBC 2019
Country/TerritoryGermany
CityBerlin
Period23/07/1927/07/19
Internet address

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