Abstract-Fractal time series analysis methods are commonly used for analyzing center of pressure (COP) signals with the goal of revealing the underlying neuromuscular processes for upright stance control. The use of fractal methods is often coupled with the assumption that the COP is an instance of fractional Gaussian noise (fGn) or fractional Brownian motion (fBm). Our purpose was to evaluate the applicability of the fGn-fBm framework to the COP in light of several characteristics of COP signals revealed by a new method, adaptive fractal analysis (AFA). AFA quantifies how the variance of the residuals to fits of a globally smooth trend signal scales with the time scale at which the fits are performed. Application of AFA to COP signals revealed that there are potentially three fractal scaling regions in the COP as opposed to one as expected from a pure fGn or fBm process. The scaling region at the fastest scale was antipersistent and spanned~30-90 ms, the intermediate was persistent and spanned~200 ms-1.9 s, and the slowest was anti-persistent and spanned~5-40 s. The intermediate fractal scaling region was the most clearly defined, but it only contributed around 11% of the total spectral energy of the COP signal, indicating that other features of the COP signal contribute more importantly to the overall dynamics. Also, more than half of the Hurst exponents estimated for the intermediate region were greater than the theoretically expected range [0,1] for fGn-fBm processes. These results suggest the fGn-fBm framework is not appropriate for modeling COP signals. ON-OFF intermittency might provide a better modeling framework for the COP, and multiscale approaches may be more appropriate for analyzing COP data.

The authors present a tutorial description of adaptive fractal analysis (AFA). AFA utilizes an adaptive detrending algorithm to extract globally smooth trend signals from the data and then analyzes the scaling of the residuals to the fit as a function of the time scale at which the fit is computed. The authors present applications to synthetic mathematical signals to verify the accuracy of AFA and demonstrate the basic steps of the analysis. The authors then present results from applying AFA to time series from a cognitive psychology experiment on repeated estimation of durations of time to illustrate some of the complexities of real-world data. AFA shows promise in dealing with many types of signals, but like any fractal analysis method there are special challenges and considerations to take into account, such as determining the presence of linear scaling regions.

These preliminary data indicate that those who do not later sustain an ACL injury exhibit a stronger functional connection between a cortical sensory-motor region and a cerebellar region responsible for balance and coordination. These findings may help to guide development of brain-driven biofeedback training that optimizes and promotes adaptive neuroplasticity to reduce motor coordination errors and injury risk.

Purpose The purpose of this study was to evaluate the utility of postural sway variability as a potential assessment to detect altered postural sway in youth with symptoms related to a concussion. Methods Forty participants (20 who were healthy and 20 who were injured) aged 10 to 16 years were assessed using the Balance Error Scoring System (BESS) and postural sway variability analyses applied to center-of-pressure data captured using a force plate. Results Significant differences were observed between the 2 groups for postural sway variability metrics but not for the BESS. Specifically, path length was shorter and Sample and Renyi Entropies were more regular for the participants who were injured compared with the participants who were healthy (P < .05). Conclusion The results of this study indicate that postural sway variability may be a more valid measure than the BESS to detect postconcussion alterations in postural control in young athletes.

Context: A limiting factor for reducing anterior cruciate ligament injury risk is ensuring that the movement adaptions made during the prevention program transfer to sport-specific activity. Virtual reality provides a mechanism to assess transferability, and neuroimaging provides a means to assay the neural processes allowing for such skill transfer. Objective: To determine the neural mechanisms for injury risk–reducing biomechanics transfer to sport after anterior cruciate ligament injury prevention training. Design: Cohort study. Setting: Research laboratory. Participants: Four healthy high school soccer athletes. Interventions: Participants completed augmented neuromuscular training utilizing real-time visual feedback. An unloaded knee extension task and a loaded leg press task were completed with neuroimaging before and after training. A virtual reality soccer-specific landing task was also competed following training to assess transfer of movement mechanics. Main Outcome Measures: Landing mechanics during the virtual reality soccer task and blood oxygen level–dependent signal change during neuroimaging. Results: Increased motor planning, sensory and visual region activity during unloaded knee extension and decreased motor cortex activity during loaded leg press were highly correlated with improvements in landing mechanics (decreased hip adduction and knee rotation). Conclusion: Changes in brain activity may underlie adaptation and transfer of injury risk–reducing movement mechanics to sport activity. Clinicians may be able to target these specific brain processes with adjunctive therapy to facilitate intervention improvements transferring to sport.

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Background Athletes who return to sport after anterior cruciate ligament reconstruction are at increased risk of future ACL injury. Altered coordination of lower extremity motion may increase this risk. The purpose of this study was to prospectively determine if altered lower extremity coordination patterns exist in athletes who go on to sustain a 2nd anterior cruciate ligament injury. Methods Sixty-one female athletes who were medically cleared to return to sport after anterior cruciate ligament reconstruction were included. Hip-ankle coordination was assessed prior to return to sport with a dynamic postural coordination task. Within 12 months, 14 patients sustained a 2nd ACL injury. Fourteen matched subjects were selected for comparative analysis. Cross-recurrence quantification analysis characterized hip-ankle coordination patterns. A group × target speed (slow vs. fast) × leg (involved vs. uninvolved) analysis of variance was used to identify coordination differences. Findings A main effect of group (p = 0.02) indicated that the single injury group exhibited more stable hip-ankle coordination [166.2 (18.9)] compared to the 2nd injury group [108.4 (10.1)]. A leg × group interaction was also observed (p = .04). The affected leg of the single injury group exhibited more stable coordination [M = 187.1 (23.3)] compared to the affected leg of the 2nd injury group [M = 110.13 (9.8)], p = 0.03. Interpretation Hip-ankle coordination was altered in female athletes who sustained a 2nd anterior cruciate ligament injury after return to sport. Failure to coordinate lower extremity movement in the absence of normal knee proprioception may place the knee at high-risk.

Prospective evidence indicates that functional biomechanics and brain connectivity may predispose an athlete to an anterior cruciate ligament injury, revealing novel neural linkages for targeted neuromuscular training interventions. The purpose of this study was to determine the efficacy of a real-time biofeedback system for altering knee biomechanics and brain functional connectivity. Seventeen healthy, young, physically active female athletes completed 6 weeks of augmented neuromuscular training (aNMT) utilizing real-time, interactive visual biofeedback and 13 served as untrained controls. A drop vertical jump and resting state functional magnetic resonance imaging were separately completed at pre-and posttest time points to assess sensorimotor adaptation. The aNMT group had a significant reduction in peak knee abduction moment (pKAM) compared to controls (p = .03, d = 0.71). The aNMT group also exhibited a significant increase in functional connectivity between the right supplementary motor area and the left thalamus (p = .0473 after false discovery rate correction). Greater percent change in pKAM was also related to increased connectivity between the right cerebellum and right thalamus for the aNMT group (p = .0292 after false discovery rate correction, r 2 = .62). No significant changes were observed for the controls (ps > .05). Our data provide preliminary evidence of potential neural 2 of 15 | DIEKFUSS Et al. ORCID Jed A. Diekfusshttps://orcid.org/0000-0003-3835-363X Dustin R. Grooms https://orcid.org/0000-0001-6102-8224