This study will establish a machine-learning algorithm to predict KAM using IMU sensors during stair ascent and descent; and then conduct a three-arm randomized controlled trial to compare the biomechanical and clinical difference between patients receiving a course of conventional laboratory-based stair retraining, sensor-based stair retraining, and walking exercise control (i.e., walking exercise without gait retraining). The investigators hypothesise that the wearable IMUs will accurately predict KAM during stair negotiation using machine-learning algorithm, with at least 80% measurement agreement with conventional calculation of KAM. The investigators also hypothesise that patients randomized to the laboratory-based and sensor-based stair retraining conditions would evidence similar (i.e., weak and non-significant differences) reduction in KAM (primary outcome) and an improvement of symptoms (secondary outcomes), but that these subjects would evidence larger reductions in KAM than subjects assigned to the walking exercise control condition.
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Change in knee adduction moment (KAM)
Timeframe: baseline and 7 weeks