Real-time biofeedback directly on the knee adduction moment is a promising option for encouraging gait modifications to reduce knee loading, however only when combined with specific instructions on how to modify the gait.

To evaluate muscle activation patterns and co-contraction around the knee in response to walking with modified gait patterns in patients with medial compartment kneeosteoarthritis (KOA). Design: 40 medial KOA patients walked on an instrumented treadmill. Surface EMG activity from seven knee-spanning muscles (gastrocnemius, hamstrings, quadriceps), kinematics, and ground reaction forces were recorded. Patients received real-time visual feedback on target kinematics to modify their gait pattern towards three different gait modifications: Toe-in, Wider steps, Medial Thrust. The individualized feedback aimed to reduce their first peak knee adduction moment (KAM) by ≥10%. Changes in muscle activations and medial/lateral co-contraction index during the loading response phase (10-35% of the gait cycle) were evaluated, for the steps in which ≥10% KAM reduction was achieved. Results: Data from 30 patients were included in the analyses; i.e. all who could successfully reduce their KAM in a sufficient number of steps by ≥10%. When walking with ≥10% KAM reduction, Medial Thrust gait (KAM −31%) showed increased flexor activation (24%), co-contraction (17%) and knee flexion moment (35%). Isolated wider-step gait also reduced the KAM (−26%), but to a smaller extent, but without increasing muscle activation amplitudes and co-contraction. Toe-in gait showed the greatest reduction in the KAM (−35%), but was accompanied by an increased flexor activation of 42% and hence an increased co-contraction index. Conclusion: Gait modifications that are most effective in reducing the KAM also yield an increase in co-contraction, thereby compromising at least part of the effects on net knee load.

Biofeedback training to encourage gait modifications is feasible and leads to short-term benefits. However, at follow-up, reductions in KAM were less pronounced in some participants suggesting that to influence progression of KOA in the longer term, a permanent regime to reinforce the effects of the training program is needed. Trial number: ISRCTN14687588.

Background: The assessment of functional recovery of patients after a total knee replacement includes the quantification of gait deviations. Comparisons to comfortable gait of healthy controls may incorrectly suggest biomechanical gait deviations, since the usually lower walking speed of patients already causes biomechanical differences. Moreover, taking peak values as parameter might not be sensitive to actual differences. Therefore, this study investigates the effect of matching walking speed and full-waveform versus discrete analyses. Methods: Gait biomechanics of 25 knee replacement patients were compared to 22 controls in two ways: uncorrected and corrected for walking speed employing principal component analyses, to reconstruct control gait biomechanics at walking speeds matched to the patients. Ankle, knee and hip kinematics and kinetics were compared over the full gait cycle using statistical parametric mapping against using peak values. Findings: All joint kinematics and kinetics gait data were impacted by applying walking speed correction, especially the kinetics of the knee. The lower control walking speeds used for reference generally reduced the magnitude of differences between patient and control gait, however some were enlarged. Full-waveform analysis identified greater deviating gait cycle regions beyond the peaks, but did not make peak value analyses redundant. Interpretation: Matching walking speed of controls affects identification of gait deviations in patients with a total knee replacement, reducing deviations confounded by walking speed and revealing hidden gait deviations related to possible compensations. Full-waveform analysis should be used along peak values for a comprehensive quantification of differences in gait biomechanics.