Human gait using locked and stance control mode knee ankle foot orthoses : optimising data analysis techniques to detect and quantify gait deviations

摘要

Knee-Ankle-Foot Orthoses (KAFOs) potentially benefit a large range of patient populations with quadriceps weakness and knee instability. In the UK the most common prescribed is a locked-knee device, where the knee is locked in extension at all times, which have been shown to introduce secondary gait deviations, such as vaulting, hip hiking and circumduction. Stance control KAFOs, which lock the knee during stance but permit flexion during swing have been shown to reduce gait deviations as well as increase walking speed and efficiency. [1] The Gait Deviation Index (GDI) [2] is a metric distilled from a walking dataset to indicate the extent to which a person’s gait deviates from a control. To our knowledge the GDI has not previously been demonstrated to quantify the effects of assistive devices, such as KAFOs. In addition, calculation of the GDI has often required substantial manual processing of data, which is time consuming and subject to human error. The aims of this study were to conduct a comparison of walking biomechanics whilst using a KAFO in both locked and stance control modes, and also to develop a data processing utility to automatically calculate and report the Gait Deviation Index, as well as more traditional kinematic and spatial temporal data.