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Predicting grip strength and key pinch using anthropometric data, DASH questionnaire and wrist range of motion

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PurposeThe objective of this study was to examine the influence of anthropometric data, occupational manual strain, DASH (disability of arm, shoulder and hand) score and range of motion (ROM) on grip strength and key pinch. An additional goal was to develop models that enable the prediction of hand...

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Hauptverfasser: Klum, Matthias Peter (VerfasserIn) , Wolf, Maya Barbara (VerfasserIn) , Bruckner, Thomas (VerfasserIn) , Unglaub, Frank (VerfasserIn)
Dokumenttyp: Article (Journal)
Sprache:Englisch
Veröffentlicht: December 2012
In: Archives of orthopaedic and trauma surgery
Year: 2012, Jahrgang: 132, Heft: 12, Pages: 1807-1811
ISSN:1434-3916
DOI:10.1007/s00402-012-1602-8
Online-Zugang:Verlag, Volltext: http://dx.doi.org/10.1007/s00402-012-1602-8
Verlag, Volltext: https://doi.org/10.1007/s00402-012-1602-8
Volltext
Verfasserangaben:Matthias Klum, Maya B. Wolf, Peter Hahn, Franck M. Leclère, Thomas Bruckner, Frank Unglaub
Beschreibung
Zusammenfassung:PurposeThe objective of this study was to examine the influence of anthropometric data, occupational manual strain, DASH (disability of arm, shoulder and hand) score and range of motion (ROM) on grip strength and key pinch. An additional goal was to develop models that enable the prediction of hand strength using the aforementioned parameters.MethodsNormative data generated from a healthy working population (n = 750) served as basis for the statistical analysis. Prediction models for hand strength were developed using multivariate regression analysis.ResultsGender, body weight and height, BMI and extension ROM correlate positively, age and DASH score, however, correlate negatively with grip strength and key pinch. Occupational manual strain has no influence on hand strength. The predictive power of the developed models was 68.4 % for grip strength and 57.1 % for key pinch.ConclusionsThe developed models enable the prediction of hand strength using easily obtainable data points. The models will have application in clinical practice, physiological studies, medical evidence and rehab decisions.
Beschreibung:Gesehen am 30.10.2018
Beschreibung:Online Resource
ISSN:1434-3916
DOI:10.1007/s00402-012-1602-8

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