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 contribution

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/

Conference

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

Fingerprint

Risk analysis
Brain
Aging of materials
Health
Experiments

Cite this

Ismail, H., Radwan, I., Suominen, H., Waddington, G., & Goecke, R. (2019). Sway Risk Analysis Based on Age Group Classification. In R. Barbieri (Ed.), 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (pp. 392-398). IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/EMBC.2019.8856843
Ismail, Hafsa ; Radwan, Ibrahim ; Suominen, Hanna ; Waddington, Gordon ; Goecke, Roland. / Sway Risk Analysis Based on Age Group Classification. 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). editor / Riccardo Barbieri. IEEE, Institute of Electrical and Electronics Engineers, 2019. pp. 392-398
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title = "Sway Risk Analysis Based on Age Group Classification",
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.",
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Ismail, H, Radwan, I, Suominen, H, Waddington, G & Goecke, R 2019, Sway Risk Analysis Based on Age Group Classification. in R Barbieri (ed.), 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, Institute of Electrical and Electronics Engineers, pp. 392-398, 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Berlin, Germany, 23/07/19. https://doi.org/10.1109/EMBC.2019.8856843

Sway Risk Analysis Based on Age Group Classification. / Ismail, Hafsa; Radwan, Ibrahim; Suominen, Hanna; Waddington, Gordon; Goecke, Roland.

2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). ed. / Riccardo Barbieri. IEEE, Institute of Electrical and Electronics Engineers, 2019. p. 392-398.

Research output: A Conference proceeding or a Chapter in BookConference contribution

TY - GEN

T1 - Sway Risk Analysis Based on Age Group Classification

AU - Ismail, Hafsa

AU - Radwan, Ibrahim

AU - Suominen, Hanna

AU - Waddington, Gordon

AU - Goecke, Roland

PY - 2019

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N2 - 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.

AB - 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.

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DO - 10.1109/EMBC.2019.8856843

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BT - 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

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Ismail H, Radwan I, Suominen H, Waddington G, Goecke R. Sway Risk Analysis Based on Age Group Classification. In Barbieri R, editor, 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, Institute of Electrical and Electronics Engineers. 2019. p. 392-398 https://doi.org/10.1109/EMBC.2019.8856843