Gait analysis and estimation of changes in fall risk factors

Heidi Similä, Milla Immonen, Juho Merilahti, Tuula Petakoski-Hult

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

4 Citations (Scopus)

Abstract

Falls are a major problem for older adults. A continuous gait monitoring that provides fall risk assessment would allow timely interventions aiming for preventing falls. The objective of this work was to find out whether gait variables calculated from the acceleration signal measured during walk task in the baseline assessment can predict changes in commonly used fall risk assessment scales after 12 months follow-up. Forty two subjects were measured during walk test with a triaxial acceleration sensor worn on a waist belt at the lower back near the centre of mass. The fall risk was assessed using a test protocol, which included several assessment methods. Gait analysis was able to predict a decline in ABC, BBS and GDS total scores and slower time in STS-5 after twelve-months follow-up. A subsequent study is needed to confirm the model's suitability for data recorded in everyday lives.
Original languageEnglish
Title of host publicationEngineering in Medicine and Biology Society (EMBC), 2015 37th Annual International Conference of the IEEE
PublisherInstitute of Electrical and Electronic Engineers IEEE
Pages6939 - 6942
ISBN (Electronic)978-1-4244-9271-8, 978-1-4244-9270-1
DOIs
Publication statusPublished - 2015
MoE publication typeA4 Article in a conference publication
Event37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society - Milan, Italy
Duration: 25 Aug 201529 Aug 2015
Conference number: 37

Conference

Conference37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Abbreviated titleEMBS
CountryItaly
CityMilan
Period25/08/1529/08/15

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Gait

Keywords

  • acceleration
  • accelerometers
  • estimation
  • medical services
  • muscles
  • risk management
  • standards

Cite this

Similä, H., Immonen, M., Merilahti, J., & Petakoski-Hult, T. (2015). Gait analysis and estimation of changes in fall risk factors. In Engineering in Medicine and Biology Society (EMBC), 2015 37th Annual International Conference of the IEEE (pp. 6939 - 6942). Institute of Electrical and Electronic Engineers IEEE. https://doi.org/10.1109/EMBC.2015.7319988
Similä, Heidi ; Immonen, Milla ; Merilahti, Juho ; Petakoski-Hult, Tuula. / Gait analysis and estimation of changes in fall risk factors. Engineering in Medicine and Biology Society (EMBC), 2015 37th Annual International Conference of the IEEE. Institute of Electrical and Electronic Engineers IEEE, 2015. pp. 6939 - 6942
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Similä, H, Immonen, M, Merilahti, J & Petakoski-Hult, T 2015, Gait analysis and estimation of changes in fall risk factors. in Engineering in Medicine and Biology Society (EMBC), 2015 37th Annual International Conference of the IEEE. Institute of Electrical and Electronic Engineers IEEE, pp. 6939 - 6942, 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Milan, Italy, 25/08/15. https://doi.org/10.1109/EMBC.2015.7319988

Gait analysis and estimation of changes in fall risk factors. / Similä, Heidi; Immonen, Milla; Merilahti, Juho; Petakoski-Hult, Tuula.

Engineering in Medicine and Biology Society (EMBC), 2015 37th Annual International Conference of the IEEE. Institute of Electrical and Electronic Engineers IEEE, 2015. p. 6939 - 6942.

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

TY - GEN

T1 - Gait analysis and estimation of changes in fall risk factors

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AU - Immonen, Milla

AU - Merilahti, Juho

AU - Petakoski-Hult, Tuula

PY - 2015

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N2 - Falls are a major problem for older adults. A continuous gait monitoring that provides fall risk assessment would allow timely interventions aiming for preventing falls. The objective of this work was to find out whether gait variables calculated from the acceleration signal measured during walk task in the baseline assessment can predict changes in commonly used fall risk assessment scales after 12 months follow-up. Forty two subjects were measured during walk test with a triaxial acceleration sensor worn on a waist belt at the lower back near the centre of mass. The fall risk was assessed using a test protocol, which included several assessment methods. Gait analysis was able to predict a decline in ABC, BBS and GDS total scores and slower time in STS-5 after twelve-months follow-up. A subsequent study is needed to confirm the model's suitability for data recorded in everyday lives.

AB - Falls are a major problem for older adults. A continuous gait monitoring that provides fall risk assessment would allow timely interventions aiming for preventing falls. The objective of this work was to find out whether gait variables calculated from the acceleration signal measured during walk task in the baseline assessment can predict changes in commonly used fall risk assessment scales after 12 months follow-up. Forty two subjects were measured during walk test with a triaxial acceleration sensor worn on a waist belt at the lower back near the centre of mass. The fall risk was assessed using a test protocol, which included several assessment methods. Gait analysis was able to predict a decline in ABC, BBS and GDS total scores and slower time in STS-5 after twelve-months follow-up. A subsequent study is needed to confirm the model's suitability for data recorded in everyday lives.

KW - acceleration

KW - accelerometers

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KW - muscles

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DO - 10.1109/EMBC.2015.7319988

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Similä H, Immonen M, Merilahti J, Petakoski-Hult T. Gait analysis and estimation of changes in fall risk factors. In Engineering in Medicine and Biology Society (EMBC), 2015 37th Annual International Conference of the IEEE. Institute of Electrical and Electronic Engineers IEEE. 2015. p. 6939 - 6942 https://doi.org/10.1109/EMBC.2015.7319988