Data from: Cluster analysis successfully identifies clinically meaningful knee valgus moment patterns: frequency of early peaks reflects sex-specific ACL injury incidence ...

• Main Authors: Sigurðsson, Haraldur B, Briem, Kristín
• Format: Dataset
• Language: English
• Published: Dryad 2019
• Subjects: Cluster analysis; Injury risk; Reykjavík; ACL; Data mining
• Online Access: https://dx.doi.org/10.5061/dryad.v8n3gv3; https://datadryad.org/stash/dataset/doi:10.5061/dryad.v8n3gv3

Background: Biomechanical studies of ACL injury risk factors frequently analyze only a fraction of the relevant data, and typically not in accordance with the injury mechanism. Extracting a peak value within a time series of relevance to ACL injuries is challenging due to differences in the relative timing and size of the peak value of interest. Aims/hypotheses: The aim was to cluster analyze the knee valgus moment time series curve shape in the early stance phase. We hypothesized that 1a) There would be few discrete curve shapes, 1b) there would be a shape reflecting an early peak of the knee valgus moment, 2a) youth athletes of both sexes would show similar frequencies of early peaks, 2b) adolescent girls would have greater early peak frequencies. Methods: N = 213 (39% boys) youth soccer and team handball athletes (phase 1) and N = 35 (45% boys) with 5 year follow-up data (phase 2) were recorded performing a change of direction task with 3D motion analysis and a force plate. The time series of the first ... : Knee valgus moment time seriesTime series used for a two cluster analysis of knee valgus moment waveforms based on their shape and magnitude.Sigurdsson_2019_ValgusMomentClusterAnalysis.csv ...