Biofeedback augmenting lower limb loading alters the underlying temporal structure of gait following anterior cruciate ligament reconstruction.

ABSTRACT

Biofeedback has recently been explored to target deviant lower extremity loading mechanics following anterior cruciate ligament reconstruction (ACLR) to mitigate the development of post traumatic osteoarthritis. The impact this feedback has on the structure of the stride interval dynamics-a barometer of gait system health-however, have yet to be examined. This study was designed to assess how feedback, used to alter lower-extremity loading during gait, affects the structure of stride interval variability by examining long-range stride-to-stride correlations during gait in those with unilateral ACLR. Twelve participants walked under three separate loading conditions (1) control (i.e., no cue) (2) high loading, and (3) low loading. Baseline vertical ground reaction force (vGRF) data was used to calculate a target 5% change in vGRF for the appropriate loading condition (i.e., high loading was +5% vGRF, low loading was -5% vGRF). The target for the load condition was displayed on a screen along with real-time vGRF values, prescribing changes in stride-to-stride peak vertical ground reaction forces of each limb. From time-series of stride intervals (i.e., duration), we analyzed the mean and standard deviation of stride-to-stride variability and, via detrended fluctuation analysis (i.e., DFA α), temporal persistence for each feedback condition. Both the high and low loading conditions exhibited a change toward more temporally persistent stride intervals (high loading α =0.92, low loading α = 0.98) than walking under the control condition (α = 0.78; high vs. control p = .026, low vs. control p = .001). Overall, these results indicate that altering lower extremity load changes the temporal persistence of the stride internal dynamics in ACLR individuals, demonstrating the implications of the design of gait training interventions and the influence feedback has on movement strategies.