Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/110915
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dc.contributorDepartment of Biomedical Engineering-
dc.contributorResearch Institute for Smart Ageing-
dc.contributorDepartment of Rehabilitation Sciences-
dc.contributorSchool of Fashion and Textiles-
dc.creatorLi, KJ-
dc.creatorWong, NLY-
dc.creatorLaw, MC-
dc.creatorLam, FMH-
dc.creatorWong, HC-
dc.creatorChan, TO-
dc.creatorWong, KN-
dc.creatorZheng, YP-
dc.creatorHuang, QY-
dc.creatorWong, AYL-
dc.creatorKwok, TCY-
dc.creatorMa, CZH-
dc.date.accessioned2025-02-14T07:17:45Z-
dc.date.available2025-02-14T07:17:45Z-
dc.identifier.urihttp://hdl.handle.net/10397/110915-
dc.language.isoenen_US
dc.publisherMDPI AGen_US
dc.rights© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).en_US
dc.rightsThe following publication Li, K.-J.; Wong, N.L.-Y.; Law, M.-C.; Lam, F.M.-H.; Wong, H.-C.; Chan, T.-O.; Wong, K.-N.; Zheng, Y.-P.; Huang, Q.-Y.; Wong, A.Y.-L.; et al. Reliability, Validity, and Identification Ability of a Commercialized Waist-Attached Inertial Measurement Unit (IMU) Sensor-Based System in Fall Risk Assessment of Older People. Biosensors 2023, 13, 998 is available at https://dx.doi.org/10.3390/bios13120998.en_US
dc.subjectFall risk assessmenten_US
dc.subjectWearable systemen_US
dc.subjectInertial measurement unit (IMU) sensoren_US
dc.subjectthe Mini-Balance Evaluation Systems Test (Mini-BESTest)en_US
dc.subjectCommunity-Dwelling older peopleen_US
dc.titleReliability, validity, and identification ability of a commercialized waist-attached inertial measurement unit (IMU) sensor-based system in fall risk assessment of older peopleen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume13-
dc.identifier.issue12-
dc.identifier.doi10.3390/bios13120998-
dcterms.abstractFalls are a prevalent cause of injury among older people. While some wearable inertial measurement unit (IMU) sensor-based systems have been widely investigated for fall risk assessment, their reliability, validity, and identification ability in community-dwelling older people remain unclear. Therefore, this study evaluated the performance of a commercially available IMU sensor-based fall risk assessment system among 20 community-dwelling older recurrent fallers (with a history of >= 2 falls in the past 12 months) and 20 community-dwelling older non-fallers (no history of falls in the past 12 months), together with applying the clinical scale of the Mini-Balance Evaluation Systems Test (Mini-BESTest). The results show that the IMU sensor-based system exhibited a significant moderate to excellent test-retest reliability (ICC = 0.838, p < 0.001), an acceptable level of internal consistency reliability (Spearman's rho = 0.471, p = 0.002), an acceptable convergent validity (Cronbach's alpha = 0.712), and an area under the curve (AUC) value of 0.590 for the IMU sensor-based receiver-operating characteristic (ROC) curve. The findings suggest that while the evaluated IMU sensor-based system exhibited good reliability and acceptable validity, it might not be able to fully identify the recurrent fallers and non-fallers in a community-dwelling older population. Further system optimization is still needed.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationBiosensors, Dec. 2023, v. 13, no. 12, 998-
dcterms.isPartOfBiosensors-
dcterms.issued2023-12-
dc.identifier.isiWOS:001132758300001-
dc.identifier.pmid38131758-
dc.identifier.eissn2079-6374-
dc.identifier.artn998-
dc.description.validate202502 bcrc-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_Scopus/WOSen_US
dc.description.fundingSourceRGCen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextHong Kong Polytechnic Universityen_US
dc.description.fundingTextResearch Institute for Smart Ageing, The Hong Kong Polytechnic Universityen_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryCCen_US
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