Massoud Saleh, Ismaiel Ebrahim, Massoud Rasha, Khadour Leila, Al-Mawaldi Moustafa
Department of Biomedical Engineering, Faculty of Mechanical and Electrical Engineering, Damascus University, Damascus 86, Syria.
Department of Medicine and Surgery, University of Parma, 43125, Parma, Italy.
Sci Rep. 2025 Jan 8;15(1):1372. doi: 10.1038/s41598-025-85172-2.
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. The FLS-GIS utilizes hierarchical feature fusion and fuzzy logic models to systematically evaluate and score gait patterns, focusing on spatial and temporal features across the hip, knee, and ankle joints. The two FLS types-1 (FLS-GIS-T1) and type-2 (FLS-GIS-T2) indices, respectively, were implemented to comprehensively study gait profiles. Starting with the gait parameters of all subjects, the changes in gait parameters in post-surgery children reflect significant improvements in gait dynamics, bringing walking patterns in CP children closer to those of their typically healthy peers. Both FLS-GIS-T1 and FLS-GIS-T2 demonstrated significant improvements in post-surgery evaluations compared to pre-surgery assessments, with p values < 0.05 and < 0.001, respectively, when compared to traditional indices. The proposed FLS-based index offers clinicians a robust and standardized gait evaluation tool, characterized by a fixed range of values, enabling consistent assessment across various gait conditions.
步态分析对于识别与正常步态周期的功能偏差至关重要，对于脑瘫（CP）等运动障碍的个体化治疗也必不可少。本研究的主要贡献是引入了一种基于多模态模糊逻辑系统的步态指数（FLS - GIS），旨在为健康儿童和患有CP的儿童在手术前后的步态模式提供数值评分。本研究检查并评估了接受跟腱延长术的CP患儿的手术效果。FLS - GIS利用分层特征融合和模糊逻辑模型来系统地评估步态模式并进行评分，重点关注髋、膝和踝关节的空间和时间特征。分别实施了两种类型的FLS，即1型（FLS - GIS - T1）和2型（FLS - GIS - T2）指数，以全面研究步态概况。从所有受试者的步态参数开始，术后儿童步态参数的变化反映了步态动力学的显著改善，使CP儿童的行走模式更接近其健康同龄人。与术前评估相比，FLS - GIS - T1和FLS - GIS - T2在术后评估中均显示出显著改善，与传统指数相比，p值分别<0.05和<0.001。所提出的基于FLS的指数为临床医生提供了一种强大且标准化的步态评估工具，其特点是具有固定的值范围，能够在各种步态条件下进行一致的评估。
