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 (...
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Published in | Scientific reports Vol. 15; no. 1; pp. 1372 - 10 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
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08.01.2025
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Abstract | 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. |
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AbstractList | 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. 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.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. 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. Abstract 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. |
ArticleNumber | 1372 |
Author | Massoud, Rasha Ismaiel, Ebrahim Massoud, Saleh Al-mawaldi, Moustafa Khadour, Leila |
Author_xml | – sequence: 1 givenname: Saleh surname: Massoud fullname: Massoud, Saleh organization: Department of Biomedical Engineering, Faculty of Mechanical and Electrical Engineering, Damascus University – sequence: 2 givenname: Ebrahim surname: Ismaiel fullname: Ismaiel, Ebrahim organization: Department of Medicine and Surgery, University of Parma – sequence: 3 givenname: Rasha surname: Massoud fullname: Massoud, Rasha email: rasha.massoud@damascusuniversity.edu.sy organization: Department of Biomedical Engineering, Faculty of Mechanical and Electrical Engineering, Damascus University – sequence: 4 givenname: Leila surname: Khadour fullname: Khadour, Leila organization: Faculty of Health Sciences, Al-Baath University – sequence: 5 givenname: Moustafa surname: Al-mawaldi fullname: Al-mawaldi, Moustafa organization: Department of Biomedical Engineering, Faculty of Mechanical and Electrical Engineering, Damascus University |
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Cites_doi | 10.1016/S0966-6362(08)70161-9 10.1016/j.gaitpost.2017.04.015 10.1186/s41983-020-00265-1 10.3390/s140203362 10.3390/pediatric14040059 10.1016/j.jbiomech.2019.109575 10.1016/j.gaitpost.2015.04.019 10.1109/91.995115 10.1016/S0966-6362(99)00047-8 10.21037/tp.2020.01.01 10.3389/fmedt.2022.901331 10.1186/s12887-023-04312-7 10.1097/01241398-200305000-00005 10.1111/j.1469-8749.2003.tb00852.x 10.3389/fresc.2024.1339856 10.1302/2058-5241.1.000052 10.2147/NDT.S235165 10.1111/ppe.12950 10.1016/j.gaitpost.2008.08.013 10.1016/j.gaitpost.2023.07.281 10.1016/j.gaitpost.2013.07.130 10.1080/10255842.2021.1946521 10.1177/2329048X18811452 10.1016/j.gaitpost.2008.05.001 10.1016/S0019-9958(65)90241-X 10.1016/0167-9457(96)00006-1 10.1016/j.gaitpost.2014.02.001 10.1016/j.gaitpost.2009.05.020 10.1016/j.gaitpost.2012.11.026 10.1016/j.gaitpost.2005.12.005 10.1109/MeMeA.2014.6860121 10.4103/ortho.IJOrtho_409_17 10.1155/2022/2622310 10.1155/2019/2085039 |
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Keywords | Cerebral palsy Hierarchical model fusion Fuzzy logic system Gait analysis Gait index |
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Snippet | Gait analysis is crucial for identifying functional deviations from the normal gait cycle and is essential for the individualized treatment of motor disorders... Abstract Gait analysis is crucial for identifying functional deviations from the normal gait cycle and is essential for the individualized treatment of motor... |
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SubjectTerms | 639/166/985 692/308/3187 692/53/2421 Achilles tendon Achilles Tendon - physiopathology Achilles Tendon - surgery Adolescent Ankle Cerebral palsy Cerebral Palsy - physiopathology Cerebral Palsy - surgery Child Children Developmental disabilities Female Fuzzy Logic Fuzzy logic system Gait Gait - physiology Gait analysis Gait Analysis - methods Gait index Hierarchical model fusion Hip Humanities and Social Sciences Humans Knee Joint - physiopathology Male Movement disorders multidisciplinary Science Science (multidisciplinary) Surgery Surgical outcomes Temporal variations |
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Title | Multimodal fuzzy logic-based gait evaluation system for assessing children with cerebral palsy |
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