A Single-IMU Wearable System with 1D U-Net for Knee Adduction Moment Waveform Reconstruction During Gait

The knee adduction moment (KAM) is an important biomechanical marker of medial knee joint loading, but conventional assessment requires laboratory-based motion analysis. This study aimed to develop and evaluate an improved inertial measurement unit (IMU)-based KAM estimation system that incorporates a one-dimensional U-Net (1D U-Net) with a gated recurrent unit (GRU) bottleneck. Gait data from 50 participants were used for model development and internal evaluation, and an independent holdout dataset collected using the same study protocol included 45 participants. Simultaneously recorded IMU signals and reference KAM obtained from motion capture-based inverse dynamics were used for training and evaluation. The model used a single IMU attached to the tibial tuberosity to reconstruct the KAM waveform during the stance phase. For peak KAM, Pearson's r values were 0.819, 0.602, and 0.621 for the training, internal validation, and holdout datasets, respectively. For KAM impulse, the corresponding values were 0.941, 0.744, and 0.745. These findings indicate that a simplified wearable system combining a single tibial IMU with a 1D U-Net incorporating a GRU bottleneck can reconstruct the KAM waveform during walking and derive clinically relevant parameters from it. Although further improvement in prediction accuracy is required, this framework may provide a practical basis for simplified screening or monitoring of medial knee loading in settings closer to routine clinical practice.