Data analysis
MTP
Data analysis consisted of segment force identification, performed in custom LabView code (National Instruments, Austin, TX, USA), followed by model kinematics and inverse dynamics, performed in Visual 3D software (C-Motion, Inc. Germantown, MD, USA).For segment force identification, pressure and shear data from the FootSTEPS device were first calibrated to the force platform and up-sampled to 100 Hz. Next, synchronized marker positions were projected onto a composite pressure footprint in order to identify the boundaries of each segment (hindfoot, forefoot, and hallux), ensuring that they matched the model endpoints [The segmental GRFs were imported into Visual 3D along with the motion capture trajectories. A previously detailed multi-segment foot model was applied [Time-normalized angle, moment, and power waveforms for the ankle, midtarsal, and MTP joints were created for visualization. The knee and hip angle waveforms were also created and visually analyzed to rule out other compensations. Range of motion (ROM) was calculated during stance for the midtarsal and MTP joints from peak plantarflexion to peak dorsiflexion angle. Joint work was calculated as the integral of the power curve during stance phase. For ankle negative work, integration started at 20% of stance phase to exclude the small positive work evident during early stance. The location of hallux COP was calculated by taking the weighted average in the anterior/posterior direction. Then, the hallux COP location was normalized to segment length prior to calculating means across subjects. Peak plantarflexion moments for the MTP and midtarsal joints were identified from the moment curves during stance phase. Similarly, the peak vertical GRF for the forefoot and hallux segments were identified during stance phase. And lastly, all metrics were averaged across the three trials so that one value per condition could be analyzed for statistics.