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Julia Freedman Silvernail, Richard E.A. van Emmerik, Katherine Boyer, Michael A. Busa and Joseph Hamill

The development of a methodology to assess movement coordination has provided gait researchers a tool to assess movement organization. A challenge in analyzing movement coordination using vector coding lies within the inherent circularity of data garnered from this technique. Therefore, the purpose of this investigation was to determine if accurate group comparisons can be made with varying techniques of vector coding analyses. Thigh–shank coordination was analyzed using a modified vector coding technique on data from 2 groups of runners. Movement coordination was compared between groups using 3 techniques: (1) linear average completed with compressed data (0°–180°) and noncompressed data (0°–360°), (2) coordination phase binning analysis; and (3) a circular statistics analysis. Circular statistics (inferential) analysis provided a rigorous comparison of average movement coordination between groups. In addition, the binning analysis provided a metric for detecting even small differences in the time spent with a particular coordination pattern between groups. However, the linear analysis provided erroneous group comparisons. Furthermore, with compressed data, linear analysis led to misclassification of coordination patterns. While data compression may be attractive as a means of simplifying statistical analysis of inherently circular data, recommendations are to use circular statistics and binning methods on noncompressed data.

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Kimmery Migel and Erik Wikstrom

study 14 reported no change in rearfoot or shank kinematics, but noted decreased segmental coupling variability between the rearfoot and the shank. Decreased variability indicates that the relationship between the segments was more stable and points to an improvement in sensorimotor control of the limb

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Eric Foch and Clare E. Milner

of this study are noted. These statistically significant differences should be placed within the context of the large range of variability within the 1 ITBS occurrence group for these joint or segment couplings. It is unclear how much coordination variability is desirable for reducing the risk of

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Wataru Kawakami, Makoto Takahashi, Yoshitaka Iwamoto and Koichi Shinakoda

10-N threshold. All kinematic data during stance phase of gait were time normalized to 100 points. Modified Vector-Coding Technique Modified vector-coding techniques quantify coupled motion between 2 segments and provide a coupling angle. 26 Four pairs of segment couplings were chosen for the

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Scott W. Ducharme and Richard E.A. van Emmerik

variable in segment couplings involving the knee joint than healthy runners. Seay and colleagues ( 2011 ) observed systematic decreases in coordination variability in runners with low back pain. Coordination variability between the pelvis and trunk was lower in runners with current low back pain compared