Multimodal fuzzy logic-based gait evaluation system for assessing children with cerebral palsy.

Gait analysis is crucial for identifying functional deviations from the normal gait cycle and is essential for the individualized treatment of motor disorders such as cerebral palsy (CP). The primary contribution of this study is the introduction of a multimodal fuzzy logic system-based gait index (FLS-GIS), designed to provide numerical scores for gait patterns in both healthy children and those with CP, before and after surgery. This study examines and evaluates the surgical outcomes in children with CP who have undergone Achilles tendon lengthening.

A type-2 fuzzy index to assess high heeled gait deviations using spatial-temporal parameters.

This paper introduces an intelligent index that numerically assesses high-heeled gait deviations. Experiments were conducted on 14 young female volunteers, and the spatial-temporal gait parameters were calculated at each heel height. A type-2 fuzzy system index was built using the baseline case (barefoot).