The learning process of gait retraining using real-time feedback in patients with medial knee osteoarthritis

The objective of this study was to investigate the learning process of knee osteoarthritis (KOA) patients learning to change their foot progression angle (FPA) over a six-week toe-in gait training program. Sixteen patients with medial KOA completed a six-week toe-in gait training program with real-time biofeedback. Patients walked on an instrumented treadmill while receiving real-time feedback on their foot progression angle (FPA) with reference to a target angle. The FPA difference (difference between target and actual FPA) was analyzed during i) natural walking, ii) walking with feedback, iii) walking without feedback and iv) walking with a dual-task at the start and end of the training program. Self-reported difficulty and abnormality and time spent walking and training were also analyzed. The FPA difference during natural walking was significantly decreased from median 6.9 to median 3.6° i.e. by 3.3° in week six (p < 0.001); adding feedback reduced FPA difference to almost zero. However the dual-task condition increased the FPA difference at week one compared to the feedback condition (median difference: 1.8°, p = 0.022), but after training this effect was minimized (median difference: 0.6°, p = 0.167). Self-reported abnormality and difficulty decreased from median 5 to 3 and from median 6 to 3 on the NRS respectively (p < 0.05). Patients with medial KOA could reduce the FPA difference during natural walking after the gait retraining program, with some evidence of a reduction in the cognitive demand needed to achieve this. Automation of adaptions might need support from more permanent feedback using wearable technologies.Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Biomechatronics & Human-Machine Contro

Effect of real-time biofeedback on peak knee adduction moment in patients with medial knee osteoarthritis: Is direct feedback effective?

Background: Gait modifications can reduce the knee adduction moment, a representation of knee loading. Reduced loading may help to slow progression of medial knee osteoarthritis. We aimed to investigate the response of patients with medial knee osteoarthritis to direct feedback on the knee adduction moment as a method for modifying the gait pattern, before and after training with specific gait modifications. Methods: Forty patients with medial knee osteoarthritis underwent 3D gait analysis on an instrumented-treadmill, while receiving real-time feedback on the peak knee adduction moment. Patients were trained with three different modifications; toe-in, wider steps and medial thrust gait. The response to real-time feedback on the knee adduction moment was measured before and after training. To evaluate the short term retention effect, we measured the changes without feedback. We also evaluated the effects on the knee flexion moment and at the hip and ankle joints. Findings: With direct feedback on the knee adduction moment, patients were initially unable to reduce the knee adduction moment. After training with specific modifications, peak knee adduction moment was reduced by 14% in response to direct feedback. Without feedback a 9% reduction in peak knee adduction moment was maintained. Hip moments were not increased with modified gait, but small increases in ankle adduction moment and knee flexion moment were observed. Interpretation: 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.Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Biomechatronics & Human-Machine Contro

Validation of wearable visual feedback for retraining foot progression angle using inertial sensors and an augmented reality headset

Background: Gait retraining interventions using real-time biofeedback have been proposed to alter the loading across the knee joint in patients with knee osteoarthritis. Despite the demonstrated benefits of these conservative treatments, their clinical adoption is currently obstructed by the high complexity, spatial demands, and cost of optical motion capture systems. In this study we propose and evaluate a wearable visual feedback system for gait retraining of the foot progression angle (FPA). Methods: The primary components of the system are inertial measurement units, which track the human movement without spatial limitations, and an augmented reality headset used to project the visual feedback in the visual field. The adapted gait protocol contained five different target angles ranging from 15 degrees toe-out to 5 degrees toe-in. Eleven healthy participants walked on an instrumented treadmill, and the protocol was performed using both an established laboratory visual feedback driven by optical motion capture, and the proposed wearable system. Results and conclusions: The wearable system tracked FPA with an accuracy of 2.4 degrees RMS and ICC=0.94 across all target angles and subjects, when compared to an optical motion capture reference. In addition, the effectiveness of the biofeedback, reflected by the number of steps with FPA value ±2 degrees from the target, was found to be around 50% in both wearable and laboratory approaches. These findings demonstrate that retraining of the FPA using wearable inertial sensing and visual feedback is feasible with effectiveness matching closely an established laboratory method. The proposed wearable setup may reduce the complexity of gait retraining applications and facilitate their transfer to routine clinical practice.Biomechatronics & Human-Machine Contro

Validation of wearable visual feedback for retraining foot progression angle using inertial sensors and an augmented reality headset

Background: Gait retraining interventions using real-time biofeedback have been proposed to alter the loading across the knee joint in patients with knee osteoarthritis. Despite the demonstrated benefits of these conservative treatments, their clinical adoption is currently obstructed by the high complexity, spatial demands, and cost of optical motion capture systems. In this study we propose and evaluate a wearable visual feedback system for gait retraining of the foot progression angle (FPA). Methods: The primary components of the system are inertial measurement units, which track the human movement without spatial limitations, and an augmented reality headset used to project the visual feedback in the visual field. The adapted gait protocol contained five different target angles ranging from 15 degrees toe-out to 5 degrees toe-in. Eleven healthy participants walked on an instrumented treadmill, and the protocol was performed using both an established laboratory visual feedback driven by optical motion capture, and the proposed wearable system. Results and conclusions: The wearable system tracked FPA with an accuracy of 2.4 degrees RMS and ICC=0.94 across all target angles and subjects, when compared to an optical motion capture reference. In addition, the effectiveness of the biofeedback, reflected by the number of steps with FPA value ±2 degrees from the target, was found to be around 50% in both wearable and laboratory approaches. These findings demonstrate that retraining of the FPA using wearable inertial sensing and visual feedback is feasible with effectiveness matching closely an established laboratory method. The proposed wearable setup may reduce the complexity of gait retraining applications and facilitate their transfer to routine clinical practice.Biomechatronics & Human-Machine Contro

The immediate effect of a soft knee brace on dynamic knee instability in persons with knee osteoarthritis

Objectives Wearing a soft knee brace has been shown to reduce self-reported knee instability in persons with knee OA. There is a need to assess whether a soft knee brace has a beneficial effect on objectively assessed dynamic knee instability as well. The aims of the study were to evaluate the effect of a soft knee brace on objectively assessed dynamic knee instability and to assess the difference in effect between a non-tight and a tight soft knee brace in persons with knee OA. Methods Thirty-eight persons with knee OA and self-reported knee instability participated in a laboratory study. A within-subject design was used comparing no brace vs brace and comparing a non-tight vs a tight brace. The primary outcome measure was dynamic knee instability, expressed by the perturbation response (PR). The PR reflects deviation in the mean knee varus-valgus angle during level walking after a controlled mechanical perturbation. Linear mixed-effect model analysis was used to evaluate the effect of a brace on dynamic knee instability. Results Wearing a brace significantly reduced the PR compared with not wearing a brace (B = -0.16, P = 0.01). There was no difference between a non-tight and a tight brace (B = -0.03, P = 0.60). Conclusion This study is the first to report that wearing a soft knee brace reduces objectively assessed dynamic knee instability in persons with knee OA. Wearing a soft brace results in an objective improvement of knee instability beyond subjectively reported improvement. Trial registration Nederlands Trial register (trialregister.nl) NTR6363Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Biomechatronics & Human-Machine Contro