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Short physical performance battery

Pilot study of a human motion capture app (MobiSPPB)

dc.contributor.authorKüppers, Lucas
dc.contributor.authorPfannenstiel, Richard
dc.contributor.authorBozorgmehr, Arezoo
dc.contributor.authorJonas, Stephan
dc.contributor.authorWeltermann, Birgitta
dc.contributor.authorReimer, Lara Marie
dc.date.accessioned2025-11-13T10:43:45Z
dc.date.available2025-11-13T10:43:45Z
dc.date.issued02.07.2025
dc.identifier.urihttps://hdl.handle.net/20.500.11811/13675
dc.description.abstractBackground: A standardized fall risk assessment can guide targeted interventions. The widely used short physical performance battery (SPPB) for mobility assessment covers balance, gait speed, and lower limb strength, but is time-consuming and requires trained raters. The newly developed video-based smartphone application called MobiSPPB provides a rater-independent SPPB assessment. This study evaluated the technical validity and reliability of the MobiSPPB app compared to the standard rater-based SPPB. In addition, the ability to detect disease-related movement patterns was investigated.
Methods: Using a standardized experimental setting, 10 healthy participants performed the SPPB with and without movement impairments simulated by an instant aging suit. Two experienced raters rated the SPPB performance, and a smartphone recorded at the same time. The MobiSPPB app analyzed videos via vision-based human motion capture techniques. Spearman's correlations, the intraclass correlation coefficient (ICC), and receiver operating characteristic curves were calculated.
Results: There was a strong correlation between the app and standard SPPB (Spearman's Correlation of 0.869, 95% confidence interval (CI) of 0.79–0.92, p < 0.001). Compared with the standard assessment, the app presented a more significant ICC in the test–retest reliability analysis (0.936, 95% CI of 0.87-0.97, p < 0.001). Detecting disease-related movement patterns achieved high accuracy in capturing severe impairments such as hemiplegia (area under the curve (AUC) 93%). Inconsistencies between the raters indicated that the app provides more objective assessments.
Conclusions: The technical validation of the MobiSPPB app was successful in a standardized experimental setting and requires further testing in clinical practice.
en
dc.format.extent12
dc.language.isoeng
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectGeriatric assessment
dc.subjectmobility assessment
dc.subjectfalls
dc.subjectfrailty
dc.subjectsarcopenia
dc.subjectshort physical performance battery
dc.subjectision-based human motion capture technology
dc.subjectmHealth
dc.subject.ddc610 Medizin, Gesundheit
dc.titleShort physical performance battery
dc.title.alternativePilot study of a human motion capture app (MobiSPPB)
dc.typeWissenschaftlicher Artikel
dc.publisher.nameSage
dc.publisher.locationThousand Oaks, CA
dc.rights.accessRightsopenAccess
dcterms.bibliographicCitation.volume2025, vol. 11
dcterms.bibliographicCitation.pagestart1
dcterms.bibliographicCitation.pageend12
dc.relation.doihttps://doi.org/10.1177/20552076251346575
dcterms.bibliographicCitation.journaltitleDigital health
ulbbn.pubtypeZweitveröffentlichung
dc.versionpublishedVersion
ulbbn.sponsorship.oaUnifundOA-Förderung Universität Bonn


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