Development of a Decision Support System for Ankle-Foot Orthosis (AFO) Design Based on Lumped Parameter Models for Human Locomotion Prediction

Abstract

This work aims to develop a decision support system (DSS) to help orthotic clinicians design AFOs to correct pathological gait patterns that result from various nerve impairments. The DSS utilizes lumped parameter models to predict key joint angles, step length, and swing and stance durations based on anthropometric data, impairment and AFO design. The predicted gait patterns by DSS were in general agreement with data from available literature. In the presented drop foot example, the DSS shows that increasing AFO stiffness would result in increased stride duration on both sides; proper AFO stiffness may result in increased stride length on both sides comparing with stride length for pathological gait without AFO. The DSS can be used by clinicians to suggest proper AFO’s mechanical properties, such as stiffness and range of motion, to help improve abnormal gait patterns resulting from underlying nerve impairments.