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dc.contributor.authorSalminen, Mikko
dc.contributor.authorPerttunen, Jarmo
dc.contributor.authorAvela, Janne
dc.contributor.authorVehkaoja, Antti
dc.date.accessioned2024-08-21T09:16:53Z
dc.date.available2024-08-21T09:16:53Z
dc.date.issued2024
dc.identifier.citationSalminen, M., Perttunen, J., Avela, J., & Vehkaoja, A. (2024). A novel method for accurate division of the gait cycle into seven phases using shank angular velocity. <i>Gait and Posture</i>, <i>111</i>, 1-7. <a href="https://doi.org/10.1016/j.gaitpost.2024.04.006" target="_blank">https://doi.org/10.1016/j.gaitpost.2024.04.006</a>
dc.identifier.otherCONVID_207853368
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/96706
dc.description.abstractBackground Accurate detection of gait events is crucial for gait analysis, enabling the assessment of gait patterns and abnormalities. Inertial measurement unit (IMU) sensors have gained traction for event detection, mainly focusing on initial contact (IC) and toe-off (TO) events. However, effective detection of other key events such as heel rise (HR), feet adjacent (FA), and tibia vertical (TBV) is essential for comprehensive gait analysis. Research question Can a novel IMU-based method accurately detect HR, TO, FA, and TBV events, and how does its performance compare with existing methods? Methods We developed and validated an IMU-based method using cumulative mediolateral shank angular velocity (CSAV) for event detection. A dataset of nearly 25,000 gait cycles from healthy adults walking at varying speeds and footwear conditions was used for validation. The method’s accuracy was assessed against force plate and motion capture data and compared with existing TO detection methods. Results The CSAV method demonstrated high accuracy in detecting TO, FA, and TBV events and moderate accuracy in HR event detection. Comparisons with existing TO detection methods showcased superior performance. The method's stability across speed and shoe variations underscored its robustness. Significance This study introduces a highly accurate IMU-based method for detecting gait events needed to divide the gait cycle into seven phases. The effectiveness of the CSAV method in capturing essential events across different scenarios emphasizes its potential applications. Although HR event detection can be further improved, the precision of the CSAV method in TO, FA, and TBV detection advance the field. This study bridges a critical gap in IMU-based gait event detection by introducing a method for subdividing the swing phase into its subphases. Further research can focus on refining HR detection and expanding the method’s utility across diverse gait contexts, thereby enhancing its clinical and scientific significance.en
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherElsevier
dc.relation.ispartofseriesGait and Posture
dc.rightsCC BY 4.0
dc.subject.othergait analysis
dc.subject.othershank angular velocity
dc.subject.otherinertial measurement unit (IMU)
dc.subject.otherevent detection
dc.titleA novel method for accurate division of the gait cycle into seven phases using shank angular velocity
dc.typearticle
dc.identifier.urnURN:NBN:fi:jyu-202408215599
dc.contributor.laitosLiikuntatieteellinen tiedekuntafi
dc.contributor.laitosFaculty of Sport and Health Sciencesen
dc.type.urihttp://purl.org/eprint/type/JournalArticle
dc.type.coarhttp://purl.org/coar/resource_type/c_2df8fbb1
dc.description.reviewstatuspeerReviewed
dc.format.pagerange1-7
dc.relation.issn0966-6362
dc.relation.volume111
dc.type.versionpublishedVersion
dc.rights.copyright© 2024 The Authors. Published by Elsevier B.V.
dc.rights.accesslevelopenAccessfi
dc.subject.ysokävely
dc.subject.ysobiomekaniikka
dc.subject.ysoliikeanalyysi
dc.format.contentfulltext
jyx.subject.urihttp://www.yso.fi/onto/yso/p3706
jyx.subject.urihttp://www.yso.fi/onto/yso/p20292
jyx.subject.urihttp://www.yso.fi/onto/yso/p24952
dc.rights.urlhttps://creativecommons.org/licenses/by/4.0/
dc.relation.doi10.1016/j.gaitpost.2024.04.006
jyx.fundinginformationThe Rehabilitation Foundation Peurunka is acknowledged as a partial funder, as they provided a small grant in support of co-author Mikko Salminen's PhD thesis work.
dc.type.okmA1


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